Machine Learning Scientist Resume Samples

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MB
M Bins
Maya
Bins
5751 Sawayn Shores
Boston
MA
+1 (555) 260 9772
5751 Sawayn Shores
Boston
MA
Phone
p +1 (555) 260 9772
Experience Experience
Detroit, MI
Machine Learning Scientist Intern
Detroit, MI
Berge Group
Detroit, MI
Machine Learning Scientist Intern
  • Exposure to current tools used by people with disabilities (screen readers and other assistive technologies)
  • Analyzing live and historic data to provide insights to the data set
  • Working with consultants and customers to help them with their problems
  • Comprehensive knowledge of machine learning/data mining and knowledge of statistics
  • Pursuing an M.S. or Ph.D. in CS, Math, Stats, or related fields
  • Cooperating and collaborating with other teams across Adobe on common project
  • Base knowledge of the W3C’s Web Content Accessibility Guidelines v2.0
Phoenix, AZ
Machine Learning Scientist
Phoenix, AZ
Lesch LLC
Phoenix, AZ
Machine Learning Scientist
  • Work closely with management, software engineering leaders, and business teams to plan catalog data improvements so as to maximize customer improvement impact
  • Develop products that can provide workflow and visualization solutions for radiology
  • Refine, improve and take ownership of existing machine learning models, systems and implementations; Refine and improve data science workflow and processes
  • Work closely with product and engineering management to influence, design and implement experiments related to product concepts
  • Work closely with software engineers and technical experts to learn existing systems and implement developed solutions
  • Track general business activity and provide clear, compelling management reports on a regular basis
  • Tracking general business activity and providing clear, compelling management reporting on a regular basis
present
Philadelphia, PA
Machine Learning Scientist Senior
Philadelphia, PA
Schneider, Blanda and Block
present
Philadelphia, PA
Machine Learning Scientist Senior
present
  • Track general business activity and provide clear, compelling management reporting on a regular basis
  • Interact frequently with team, business owners and users to maintain a good working relationship with the
  • Interact with customers and management on technical design issues and resolutions
  • Work closely with software engineering teams to test and Implements real-time models
  • Evaluate proposed initiatives and provide feedback
  • Receive assignments in the form of objectives and establishes goals to meet those objectives
  • Design, develop and evaluate innovative predictive models
Education Education
Bachelor’s Degree in Computer Science
Bachelor’s Degree in Computer Science
Johnson & Wales University
Bachelor’s Degree in Computer Science
Skills Skills
  • 3) Deployment of algorithms as realtime/ highly available services
  • 6) Completion of at least one significant project (equivalent of a great PhD research project, and/or a viable commercial product) in applied Machine Learning
  • Excellent programming skills - ability to prototype complex algorithms and collaborate with engineering team to implement the algorithms into production system
  • Demonstrated knowledge with cloud-infrastructures and configuration management tools (e.g. AWS, Ansible)
  • 7) Excellent communication skills
  • Work on large-scale datasets, focusing on creating scalable and accurate forecasting systems in versatile application fields
  • Proficiency in C++ and Python
  • Base knowledge of the W3C’s Web Content Accessibility Guidelines v2.0
  • Demonstrated knowledge with cloud-infrastructures (e.g. AWS, Google, OpenStack) and configuration management tools (e.g. Ansible)
  • Knowledge of public biological databases, tools, and repositories
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15 Machine Learning Scientist resume templates

1

Machine Learning Scientist Senior Resume Examples & Samples

  • Mine and analyze large amount of data to create directional ideas and roadmaps for business goals
  • Use statistical tools and machine learning techniques to solve business problems
  • Design, develop and evaluate innovative predictive models
  • Work closely with software engineering teams to test and Implements real-time models
  • Extract and analyze relevant information from large amounts of RH historical business data to help automate and optimize key processes for business teams
  • Help in formal definition of business problems and research potential roadmaps to solve them
  • Employ effective judgment within industry defined practices and policies in selecting methods, techniques and evaluation criteria for proposed solutions
  • Interact frequently with team, business owners and users to maintain a good working relationship with the
  • Work on complex problems where analysis of situations or data requires an in-depth evaluation of various tangible and intangible factors
  • Receive assignments in the form of objectives and establishes goals to meet those objectives
  • Act independently to determine methods and procedures on new assignments
  • Evaluate proposed initiatives and provide feedback
  • Interact with customers and management on technical design issues and resolutions
  • May prepare code migration documentation and works with release team in migrating code to environments as needed
  • Master’s or PhD degree in Statistics, Computer Science, Mathematics or equivalent strongly preferred
  • 5+ years’ of industry experience in predictive modeling and large scale data analysis
  • 5+ years’ of experience in R or equivalent statistical package is required
  • 3+ years’ of hands-on experience in statistical modeling, data mining, large data analysis and predictive modeling.Text mining is a big plus
  • 3+ years’ of experience in regression, classification and clustering methods such as GLM, LR, SVM, LVQ, SOM, Neural Networks
  • 3+ years’ of experience in using big data platforms and technologies such as: Pig, Hive, HBase, etc
  • Experience in at least one of these:Python, PERL, Matlab or Scala
  • Strong records of successes at delivering strong business results
  • Desire to work in team-oriented environment
  • Excellent communication and data presentation skills, both written and verbal
  • Ability to grasp issues quickly and make educated, critical decisions
  • Exposure to full life cycle of software development; requirements analysis, design, development, testing, implementation
2

Machine Learning Scientist Intern Resume Examples & Samples

  • Analyzing live and historic data to provide insights to the data set
  • Researching, prototyping and implementing new models and algorithms
  • Cooperating and collaborating with other teams across Adobe on common project
  • Validating and Testing Models and Algorithms
  • Working with consultants and customers to help them with their problems
3

Machine Learning Scientist Resume Examples & Samples

  • Design and develop machine learning and big data solutions for Humana Consumer Analytics
  • Implement analytical applications leveraging open source frameworks like Apache Spark
  • Comfortable working in a fast paced agile environment, closely interacting with some of industry’s best software engineers and data scientists
  • BS/MS in Computer Science or related field
  • Open source contributions or robust portfolio of shipped code at GitHub
  • Overall 4+ years’ experience implementing machine learning applications, some of it in big data environment
  • 3+ years programming experience using one or more of Java, Python, C++
  • Familiarity with Apache Spark Machine Learning libraries
  • Some programming experience with Scala (or other functional programming language) and Apache Spark implementing analytics or data processing applications
  • 3+ years experience using SQL and traditional data warehouses. Experience with Oracle and IBM Netezza preferred
  • 3+ years experience developing over Unix/Linux environment
  • Working knowledge of agile development techniques
  • Willingness to learn new technologies and comprehend unfamiliar data domains and new business processes quickly
  • Ph.D. in Computer Science or related field
  • Experience in Natural Language Processing
  • Experience with data visualization platforms like Tableau
  • Relevant certifications
  • Working knowledge of Unix/Linux system administration and shell scripting
4

Machine Learning Scientist Resume Examples & Samples

  • Prior research, data science, or engineering experience in building and implementing machine learning models/algorithms, particularly around classification, multivariate regression, pattern recognition, ranking, recommender systems, etc
  • Excellent programming skills - ability to prototype complex algorithms and collaborate with engineering team to implement the algorithms into production system
  • Driven and focused self-starters, great communicators, amazing follow-through - you aggressively tackle your work and love the responsibility of being individually empowered
5

Machine Learning Scientist Resume Examples & Samples

  • ------------
  • Gathering and analyzing data, identifying key prediction/classification problems, devising solutions and building prototypes to enforce and guide development of new genomic assays
  • Design and build data mining/analysis tools to predict the outcome/performance/success of our genomics platforms
  • Explore novel algorithmic approaches to mining of genomic variant data
  • Provide mentoring and guidance to team members on machine learning development
  • ----------
  • MSc/PhD Degree in statistics, computer science, bioinformatics or equivalent discipline
  • 7+ years of experience within the data science field
  • Expertise in predictive analytics/statistical modeling/data mining algorithms
  • Proven experience in machine learning methodologies such as regression/classification modeling, unsupervised/supervised/reinforced learning, and ensemble methods is required
  • Excellent knowledge/experience with data preparation and normalization (feature engineering) for modelling
  • Professional experience writing Python and/or Java/C code, preferably within a team environment (revision control, issue tracking, code-review)
  • Expertise in one or more of the following, or equivalent frameworks, Scikit learn, Keras, Caffe, Theano, TensorFlow, R Caret, Weka
  • Strong knowledge of Linux environments
  • Ability to build (architecture and implement) an R&D machine learning infrastructure from the ground up
  • Demonstrated knowledge with cloud-infrastructures (e.g. AWS, Google, OpenStack) and configuration management tools (e.g. Ansible)
  • Genomic/Life-Science data analysis with familiarity of existing methods and ability to prototype and implement new methodologies as needed
  • Knowledge of public biological databases, tools, and repositories
6

Machine Learning Scientist Resume Examples & Samples

  • Use statistical and machine learning techniques to create scalable solutions to address Amazon's North American Fulfillment Operations problems and identify opportunities for cost savings
  • Work closely with business teams to develop implementable models that provide real value to operational leaders
  • An MS in computer science, machine learning, data science, operational research, statistics or in a highly quantitative field
  • 1+ years of hands-on experience in development of learning and predictive systems
  • Strong programming skills with at least one object oriented language (e.g. Java) and one scripting language (e.g Python)
  • Knowledge and experience in distributed algorithm design and programming
  • A Ph.D. in computer science, machine learning, data science, operational research, statistics or in a highly quantitative field
  • 3+ years of hands-on experience in development of learning and predictive systems
  • Experience with large scale database and data warehousing systems (e.g. Redshift, Oracle)
7

Machine Learning Scientist Resume Examples & Samples

  • Algorithm implementation experience as well as the ability to modify standard algorithms (e.g. changing objectives, working-out the math, implementing and scaling)
  • Fluency with Unix systems
  • Track-record of novel algorithm development, e.g. publications in one or more of the following: KDD, WWW, NIPS, NAACL, ACL, SIGIR, EMNLP, ICML etc
  • Experience with filesystems, server architectures, and distributed systems
8

Machine Learning Scientist Resume Examples & Samples

  • Expertise in using Python, Java / C++, or other programming languages, as well as ML toolkits such as scikit-learn, Theano, Tensorflow, Keras or similar machine learning tools
  • Experience in designing and implementing information retrieval, web mining systems using Deep Learning and Neural Networks
  • Big thinker that can take broad visions and concepts and develop structured plans, actions and measurable metrics and then execute those plans
9

Principal Machine Learning Scientist Resume Examples & Samples

  • Use machine learning, NLP/NLU and statistics techniques to create scalable solutions for business problems
  • Work closely with software engineering teams to drive real-time model experiments, implementations and new feature creations
  • PHD in CS Machine Learning/NLP, Statistics, or in a highly quantitative field
  • 5+ years of hands-on experience in machine learning/NLP/NLU and large data analysis
  • 3+ years of experience using R/SAS/Python and SQL in a Linux/UNIX environment
  • 10+ years of industry experience in machine learning and large data analysis
  • Experience with deep learning and sequence modeling
  • Published research papers in NLP/NLU
10

Machine Learning Scientist Resume Examples & Samples

  • Work closely with business staff to optimize various business operations
  • A PhD in Computer Science, Machine Learning, Statistics, or in a highly quantitative field
  • 1+ years of hands-on experience in predictive modeling and big data analysis
  • 1+ years of experience using R/SAS and SQL in a Linux/UNIX environment
  • 1+ years of experience with Python
11

Machine Learning Scientist Resume Examples & Samples

  • Hands-on experiences in speech recognition, natural language understanding and machine learning
  • Research track record with peer-reviewed publications in academic conferences and journals in the related areas
  • Project management experience desired for working on cross-functional projects
12

Machine Learning Scientist Resume Examples & Samples

  • Undergraduate degree in computer science, software engineering or undergraduate degree in numerical discipline (e.g. physics, maths, engineering)
  • PhD in machine learning, statistics or in another highly quantitative/analytical field
  • Recent record of publication in internationally-leading machine learning or statistics venues (e.g. NIPS, ICML, AISTATS, UAI, JMLR, TPAMI, JASA, JRSS, Annals of Statistics)
  • Experience of working across the academic and industrial sectors
  • Hands on experience in software systems development
13

Machine Learning Scientist Resume Examples & Samples

  • Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment
  • Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems
  • Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment
  • Promote the culture of experimentation and science at Amazon
  • Degree in Computer Science, Mathematics, Physics, Statistics, or related quantitative field
  • Experience applying Machine Learning to business problems
  • Proficiency in an object-orientated programming language (C++, Java, C#, C, Perl/Ruby, etc.)
  • Proficiency with mathematical programming environments (R, Matlab, Numpy/Scipy, SAS, etc.)
  • Excellent critical thinking skills, combined with the ability to present your ideas clearly and compellingly in both verbal and written form
  • Ph.D. degree in Computer Science, Machine Learning, Data Science, or related field
14

Machine Learning Scientist Resume Examples & Samples

  • Identifying and solving hard, yet tractable problems to overcome to democratize machine learning
  • Contribute to the state-of-the-art in machine learning and share those advances through publications in top venues
  • Attract and mentor research interns
  • Help design and deliver both general and domain-specific machine learning algorithms and systems
  • Drive sound design and implementation through hands-on development
  • Work with partner teams on the integration of machine learning technology into their products
15

Machine Learning Scientist Resume Examples & Samples

  • Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own
  • Taking complex problems and the associated data and giving the answers in a concise form to assist senior executives in making key business decisions
  • 3+ year experience delivering, scaling, and owning highly successful and innovative machine learning products with your fingerprints all over them
  • Experience programming in R, Python, SQL, Java, C, C++ or C#
16

Machine Learning Scientist Resume Examples & Samples

  • Work with the team to create new deep learning and ML algorithms and applications. Drive technical vision and strategy to make DL and ML a must-have capability in delivering consumer services
  • Help to define and improve large scale Machine Learning platform that powers our Big Data products
  • Apply Natural Language Processing to understand text from forum reviews, description and interactions between users
  • Identifying suspicious transactions in online store, push message, payment
  • Clustering of users and content to enable intelligent recommendation
  • Working with engineering to build machine learning platform that covers data processing, feature engineering, and monitoring
17

Machine Learning Scientist Resume Examples & Samples

  • Use exploratory data analysis, machine learning, and statistical techniques to synthesize data into recommendations and predictions
  • Work closely with other scientists and engineers to transform concepts into production machine learning models with appropriate performance monitoring and reporting capabilities
  • Manage the ongoing improvement of models as new data, techniques, and engineering capacity allow
  • Collaborate with other Data Scientists to explore novel ways to improve and enrich our community
  • Assist in recruiting, mentoring, developing, and training other Data Scientists, and other technical roles when needed
  • 5+ years of experience working on applied machine learning projects
  • Proficiency with a scripting language such as Python
  • Ability to innovate in data science
  • MS/PhD degree in related field
  • Large scale software design and development
  • AdTech experience
18

Principal Machine Learning Scientist Resume Examples & Samples

  • PHD in CS Machine Learning, Statistics, or in a highly quantitative field
  • Solid background in statistical learning techniques
  • Strong programming skills in at least one object oriented programming language (Java, Scala, C++, Python, R, etc.). Experience in implementing the models that handle terabytes of data
  • Experience with boosting, deep learning and sequence modeling
  • Experience developing causal modeling
19

Machine Learning Scientist Resume Examples & Samples

  • Masters in computer science, statistics, neuroscience, engineering, mathematics, or physics
  • Passion for learning (new problem domains, algorithms, tools, etc.) and for analyzing data
  • Fluency in at least one of the following languages Python, Java, Scala, C/C++
  • Ph.D. degree in computer science, statistics, neuroscience, engineering, mathematics, or physics
  • Experience with advanced ML models and concepts: HMMs, CRFs, MRFs, deep learning, regularization, etc
  • 2+ years of industry experience in data science or related areas
  • Experience in fraud detection or related field
  • Experience with working on large data sets, especially with Hadoop and Spark
  • Experience with data visualization tools such as Tableau, PowerBI, etc
20

Machine Learning Scientist Resume Examples & Samples

  • Work both independently and collaboratively with other project members to develop theoretical and computational tools for a wide variety of machine learning application areas
  • Communicate research results through reports, presentations, and peer-reviewed publications
  • Mentor students, postdocs, and junior scientists in their scientific work and actively participate in their career development
  • Demonstrated record of successful proposal writing/program development
  • Experience in leading research and development in support of programs or R&D initiatives
  • Experience mentoring students and/or postdocs
  • Demonstrated technical leadership in fields relevant to the group’s core capabilities
  • Ability to obtain a Q clearance
  • Experience with image/video and signal processing
  • Experience with graph theory
  • Experience with high performance computing, GPU programming, parallel programming, cloud computing, and related methods
  • Experience with python, scikitlearn, Theano, Caffe, TensorFlow, or related modern machine learning libraries and tools
21

Machine Learning Scientist Resume Examples & Samples

  • Work closely with management, software engineering leaders, and business teams to plan catalog data improvements so as to maximize customer improvement impact
  • Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment
  • Collaborate with software engineering teams to integrate models into large-scale, highly complex Amazon production systems
  • Report results in a manner which is both statistically rigorous and compellingly relevant
  • Assist in recruiting, mentoring, developing, and training other Research Scientists as well as other technical roles when needed
  • PhD in Statistics, Computer Science, Machine Learning, Mathematics, Operational Research, Statistics or a related quantitative field
  • Theory and practice of Design of Experiments and statistical analysis of results
  • Familiar with the techniques and limitations of observational studies
  • Programming skills sufficient to extract, transform, and clean large (multi-TB) data sets
  • Proficiency in a statistics package such as SPSS, SAS, S-PLUS, or R
22

Machine Learning Scientist Resume Examples & Samples

  • (PhD or MS) in Computer Science, Statistics, Applied Math or Operations Research
  • Working knowledge of machine-learning tools (Tensorflow, Caffe, MLpack, etc.)
  • Experience in communicating technically, at a level appropriate for the audience
  • Experience with large data applications and tools (e.g. NoSQL, Apache Spark etc.)
  • Experience with statistical and mathematical modeling languages (R, Julia, or similar.)
  • SW dev skills for ML tool prototypes using Java, C++, C#, or Python
23

Machine Learning Scientist Resume Examples & Samples

  • Ph.D. degree
  • 4+ years of experience in data mining/predictive modeling
  • 4+ years of experience with Linux/Unix tools
  • 4+ years of experience in scripting for data analysis (Perl, Awk, Python, etc)
  • 5+ years of experience with data analysis package (R, SAS, Matlab, etc)
  • Ph.D. in an analytical area such as Mathematics, Statistics, Computer Science, Physics, Engineering or similar
  • Experience with time series forecasting
  • Programming experience in C++ or Java
  • Experience with SQL databases to manage and analyze large data sets
24

Machine Learning Scientist Resume Examples & Samples

  • A PhD in machine learning, information science, engineering, statistics or a highly quantitative field. Masters with equivalent experience will be considered
  • Programming, prototyping and scripting skills (Oracle, SQL, Hive, Pig, SAS, R, Weka, Python)
  • Writing, communication and presentation skills
  • 3 years of post-PhD experience
25

Machine Learning Scientist Resume Examples & Samples

  • Build mathematical models for demand forecasting at various levels
  • Prototype these models by using software languages such as Python or sometimes high-level modeling languages such as MATLAB or R. You will collaborate closely with a software team to transform prototypes into production code
  • Gather data required for analysis and mathematical model building by writing scripts and database queries. You will interact with data in a Hadoop environment, Oracle or Redshift databases and AWS storage technologies (such as S3)
  • Use various distributed computing frameworks including Hadoop, Spark, Scala, and EMR
  • Ph.D. in Machine Learning, Data Mining, Statistics, Applied Mathematics, or a related field, or a Master’s degree in Machine Learning, Data Mining, Statistics, Applied Mathematics or a related field and 2 or more years of relevant industry experience
  • 2+ years of experience in machine learning with domain knowledge and experience in the following areas: data-driven statistical modeling, discriminative methods, feature extraction and analysis, supervised learning
  • Fluency in a software programming language such as Python, Java, C++, etc
  • Fluency in a high-level modeling language such as MATLAB, Stata, or R
  • 2+ years of experience with data extraction and analysis
  • Familiarity with distributed computing frameworks e.g. Spark, Scala, etc. Experience in Python is helpful
  • Experience with large data sets (10 million+ rows)
26

Machine Learning Scientist Resume Examples & Samples

  • Design predictive control-based models and systems for flow-control, inventory control, reactive capacity control and cost-management for the North American Supply Chain
  • Collaborate with software engineering teams to integrate these systems and models into large-scale, highly complex Amazon production systems
  • A degree PhD in Computer Science, Statistics, Applied Math or Operations Research
  • SW dev skills for ML tool prototypes using Java, C++, C\#, or Python
  • Extensive experience using production machine-learning tools (Tensorflow, Caffe, MLpack, etc.)
27

Machine Learning Scientist Resume Examples & Samples

  • Design and implement sophisticated image processing and analysis algorithms
  • Carry out research on machine learning algorithms including deep learning
  • Develop machine learning and pattern recognition algorithms for medical imaging applications, including detecting and classifying objects in 2D and 3D medical images
  • Develop products that can provide workflow and visualization solutions for radiology
  • Investigate and evaluate existing technologies
  • Communicate ideas and brainstorm with fellow researchers on ideas and problems
  • Design and implement appropriate tools to analyze results and optimize development
  • Create software tools for effective algorithm training and testing, perform software validation and verification, maintain programs including bug-fixes & modifications
  • Proficiency at C/C++ programming in a Windows environment is required
  • Experience with Caffe or TensorFlow is highly desired, experience with MATLAB is a plus
  • Advanced degree with research experience in machine learning and/or image analysis is beneficial
  • Good documentation practices, writing and communication skills are required
  • Extensive prior experience with machine learning algorithms (including deep learning) is required
  • Prior experience with image processing algorithm development with medical imaging applications is beneficial; extensive background knowledge in computer vision is also beneficial
  • Prior experience with GPU programming (e.g. CUDA) and GPU optimization is very beneficial
  • Prior experience with breast imaging modality is beneficial
28

Machine Learning Scientist Resume Examples & Samples

  • Ph.D. in Machine Learning, Data Mining, Statistics, Applied Mathematics, or a related field
  • Experience with an object oriented programming language such as Python, C++, Java, etc
  • Experience in a high-level modeling language such as MATLAB, R, Stata, etc
  • Applied experience building/evaluating predictive models
29

Machine Learning Scientist Resume Examples & Samples

  • Use statistical and machine learning techniques to develop scalable solutions to address Amazon Payments Products business problem and improve ad serving platform
  • Conduct A/B tests to evaluate new learning algorithms and features
  • Strong programming skills with at least one object oriented language (e.g. Java) and one scripting language (e.g. Python)
  • A PhD in computer science, machine learning, statistics or in a highly quantitative field
30

Machine Learning Scientist Resume Examples & Samples

  • Develop and explore novel algorithms for designing and analyzing genomic assays
  • Prepare and deliver scientific presentations based on technical progress and achievements
  • MSc or PhD Degree in statistics, computer science, bioinformatics or equivalent combination of education and experience
  • 7+ years of experience within the bioinformatics and data science field
  • Excellent data analysis skills, including development of novel/custom algorithms for interpretation of NGS data
  • High knowledge of public biological databases, tools, and repositories
  • Experience in machine learning methodologies such as regression/classification modeling, unsupervised/supervised/semi-supervised learning, and ensemble methods
  • Professional experience writing Python, Java, or C code, preferably within a team environment (revision control, issue tracking, code-review)
  • Strong knowledge of Linux and HPC environments
  • Demonstrated knowledge with cloud-infrastructures and configuration management tools (e.g. AWS, Ansible)
  • Experience in next-generation sequencing analysis of cancer genomes
31

Machine Learning Scientist Resume Examples & Samples

  • Design, develop and evaluate innovative models for predictive learning
  • Work closely with project teams to drive model experiments, implementations, and new features
  • BA/BS in Statistics, Computer Science Machine Learning, or other highly quantitative field
  • Strong grasp of machine learning and data analytics techniques
  • Strong software development skills (C/C++, Java, or Python)
  • 1+ years of hands-on experience in machine learning, recommendation systems, pattern recognition, large-scale data mining or artificial intelligence
  • Background in natural language processing or computer vision
32

Machine Learning Scientist Resume Examples & Samples

  • 1+ year industry or academic experience in Machine Learning
  • 5 years of industry or academic experience implementing algorithms in C++/C#/Java/Python or similar language
  • Ph.D. in Machine Learning or related area
33

Machine Learning Scientist Resume Examples & Samples

  • Work closely with the business to understand the problem space, identify the opportunities and formulate the problems
  • Interact with software engineering teams to build data platforms for large-scale data analysis and modeling
  • 5+ years of hands-on experience in deep learning, predictive modeling and analysis
  • Experience in using R, MATLAB or other statistical software
  • PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics or in another highly quantitative field
34

Machine Learning Scientist Resume Examples & Samples

  • Innovate new machine learning approaches for advertising targeting and optimization
  • Research and implement novel experimental design and measurement methodologies
  • Establish scalable, efficient, automated processes for large scale machine learning
  • Leverage petabyte scale data in strategic analysis for new monetization strategies, products and business directions
  • PhD focused on Statistical/Machine Learning in Computer Science or Statistics or related disciplines with domain knowledge and experience in the following areas
  • Statistics, machine learning, data mining
  • Algorithms, optimization, auction theory
  • Experience with large data sets, experiment design and analysis
  • MS may be substituted with 4+ years of industrial experience in Machine Learning
  • 2+ years of post-graduate experience in Predictive Modeling, Machine Learning, or similar function
  • Proficient in Python, Scala, or similar scripting language
  • Proficient in Pig and Hive
  • Experience working with advertising, retail or e-commerce data
35

Machine Learning Scientist Resume Examples & Samples

  • Use statistical and machine learning techniques to create scalable MT and text understanding systems
  • Design, development and evaluation of highly accurate and innovative models for translation and for language analysis and generation
  • Work closely with software engineering teams to drive large-scale and real-time model implementations and new feature capabilities
  • Establish scalable, efficient, automated processes for large-scale data analysis, model development, model validation and model implementation
  • MS or PhD in Computer Science, Computational Linguistics, Machine Learning, Statistics or in another highly quantitative field
  • 3+ years of hands-on experience in data-driven predictive modeling and analysis in MT, NLP or other related language technology areas
  • Strong implementation skills in Java, C++ (or other high-level programming language) as well as Python or similar scripting languages
  • Experience in R&D in large-scale NLP systems in a large industrial or government environment
  • Demonstrated independent scientific thinking and/or a track record of thought leadership and contributions that have advanced the field
  • Established publication record in MT, NLP and/or related fields
  • A curiosity about problems that seem impossible to solve and a drive to think outside of the box to invent what hasn't been invented yet
36

Big Data Machine Learning Scientist Resume Examples & Samples

  • Design and develop machine learning/AI and big data solutions to enable Humana enterprise strategy
  • Possess in depth understanding of various machine learning and predictive modeling algorithms. Able to tweak core design/implementation to enable efficient parallelism within big data domain
  • Evaluate various machine learning algorithms and recommend the best ones under various scenarios, considering business goal along with field activation and implementation challenges associated with big data platforms
  • Comfortable working in a fast paced agile environment, closely interacting with business, software engineers and other machine learning scientists
  • Provide hands-on expertise and mentorship to other data scientists
  • Excellent presentation skills and ability to adjust the content and level of detail to appropriate audiences (technical / non-technical / business / executives)
  • Significant passion in not only carrying out the core machine learning and technical aspects of the work, but also in being a change-agent ascertaining that the work is appropriately transformed into actions
  • 3+ years of hands-on experience in applying core Machine Learning methodologies: Artificial Neural Networks/ Deep Learning, Support Vector Machines, Matrix Factorization, Natural Language processing, Decision trees, Classification, Clustering, Predictive Analytics, Regression
  • 3+ years of Machine Learning/AI programming experience with Python, Java, C++, Scala, R or similar stack
  • 5+ years of data analytics experience
  • Advance degree in quantitative field, computer science, applied mathematics, statistics or related field
37

Machine Learning Scientist Resume Examples & Samples

  • Analyze and extract relevant information from large amounts of AWS Support data to help automate and optimize key processes
  • Design, develop and evaluate highly innovative predictive ML models
  • MS in Machine Learning, Computer Science, Statistics, Applied Mathematics or in another highly quantitative field
  • 5+ years of hands-on experience in machine learning learning, predictive modeling and analysis
  • Proficiency in Java, C++ (or other high-level programming language) as well as Python (or similar scripting language) and SQL
  • Experience using R, MATLAB or other statistical software
  • Excellent communication and data presentation skills
  • A natural curiosity and desire to learn and adopt
  • PhD in Machine Learning, Computer Science, Statistics, or Applied Mathematics
38

Machine Learning Scientist Resume Examples & Samples

  • Doctoral Degree in Computer Science, Electrical Engineering or related field
  • Experience or knowledge in building predictive modelling and analysis system using Neural Networks, Data Mining, and Machine Learning technologies
  • 5-10 years of experience in building large-scale Machine Learning systems
  • Solid research track record with peer-reviewed publications in top academic conferences and journals in the related areas
  • Proficiency in, at least, one modern programming language such as C, C++, Java, or Python
  • Experience with programming on Amazon Web Services
  • Experience gathering, storing, and leveraging “big data” for business intelligence and prediction use cases
39

Machine Learning Scientist Resume Examples & Samples

  • A PhD in Computer Science, Applied Math, Statistics, Electrical Engineering or a highly quantitative field
  • Hands-on experience developing and implementing Machine Learning algorithms and models
  • At least 2 years of relevant experience
  • Programming and prototyping skills (Java/C++ and R/MATLAB/Python)
  • Solid communication and data presentation skills
  • A track record of innovating in Machine Learning algorithms and applications
  • Programming skills sufficient to extract, transform, and clean large (multi-TB) data sets in a Unix/Linux environment
  • Superior verbal and written communication skills,
  • Proven software development skills and experience
  • Ability to own projects end-to-end
40

Machine Learning Scientist Intern Resume Examples & Samples

  • Master's degree Working towards completion of PhD program
  • Practical experience in relevant areas such as AI, applied machine learning, vision/NUI, big data analytics
  • Self-starter who can dive in and define a problem set, work with a fast paced internal startup
  • Be able to create requirements and chunk out work based on iterative discoveries
  • Coding experience in C/C++/Java/C#, Python
  • Experience with MATLAB and R
41

Machine Learning Scientist Resume Examples & Samples

  • 1) Employ the existing (and develop new) Machine Learning algorithms that can find patterns in large multi-modal data
  • 2) Innovate and provide solutions for the business (e.g., by translating complex commercial problems to Machine Learning problems)
  • 3) Be an active member of teams that provide the business with data-driven apps, insight and strategies
  • 4) Participate in, lead, and create cross-functional projects and training
  • 6) Review, direct, guide, inspire the research of more junior scientists in the team
  • 1) Scientific expertise and applied experience in Machine Learning (ideally, a combination of excellent academic research and high-impact commercial experience)
  • 2) In depth understanding of common Machine Learning algorithms (e.g., for classification, regression and clustering)
  • 3) Track record in advanced topics of Machine Learning (e.g., Bayesian inference, hierarchical models, deep learning, Gaussian processes, causal inference, graph theory, etc.)
  • 4) Advanced programming skills in Python and/or R (and their related data processing, Machine Learning, and visualisation libraries)
  • 5) Practical experience in preparing data for Machine Learning (e.g., using SQL and/or NoSQL technologies)
  • 6) Completion of at least one significant project (equivalent of a great PhD research project, and/or a viable commercial product) in applied Machine Learning
  • 7) Excellent communication skills
  • 1) Integration of Machine Learning algorithms with big-data platforms (e.g., Spark) and high-performance computing ecosystems (e.g., CUDA)
  • 2) Programming in C++, Java
  • 3) Deployment of algorithms as realtime/ highly available services
  • 4) Integration with front-end systems (e.g., HTML5/ native mobile apps)
  • 5) Employing Machine Learning in collaborative commercial settings (e.g., using DevOps methodologies and tools such as GitHub), ideally, in collaboration with product development teams
  • 6) Publication in the top scientific journals and conferences
  • 7) Leading scientific projects
  • 8) Publication record in (and willingness to represent AIG in) scientific conferences such as NIPS, ICML, ICLR, AAAI…
42

Machine Learning Scientist Resume Examples & Samples

  • Manage the development of machine learning techniques (CNN, Deep Learning, decision logic) for various imaging-based detection systems in software packages and programming languages such as Matlab, GPU code (e.g. Cuda), C/C++, Java
  • Serve at Subject Matter Expert (SME) for technical knowledge of machine learning techniques and image processing programs or applications as directed, representing Smiths Detection and providing feedback to internal teams
  • Provide engineering support of key testing activities, including support of laboratory and field testing activities
  • Create R&D funding proposals, information packages, and presentations in support of external funded R&D efforts
  • Interact with external technical personnel, industry groups, testing standards groups, selected customers, and internal management to provide feedback into the product development and design efforts
  • Collect sample images, library data, and technical information to support algorithm development projects
  • Lead U.S.-based testing and development of detection systems and software including executing test plans and experiments in a laboratory setting
  • Must comply with and ensure department compliance with Company health, safety and environmental policies
  • Must comply with all applicable U.S. export and security regulations
43

Machine Learning Scientist Resume Examples & Samples

  • Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency
  • Degree in Applied Mathematics, Statistics, Machine Learning, Data Science or a related quantitative field
  • Experience developing sophisticated models using advanced mathematics and statistics in academic or industry environments
  • Proficient in a programming language (Python, C++, Java, C#, C, Perl/Ruby, etc.)
  • Proficient with mathematical programming environments (R, Matlab, Numpy/Scipy, SAS, etc.)
  • Excellent written and spoken English
  • Ph.D. degree in Applied Mathematics, Statistics, Machine Learning, Data Science or a related quantitative field
44

Data Analytics / Machine Learning Scientist Resume Examples & Samples

  • Research, design and prototype novel models based on machine learning, data mining, and statistical modeling in order to solve hard analytics problems, where the problems may range from exploratory to highly applied
  • Keep abreast of the latest developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand
  • Collaborate closely with university partners and other scientists and engineers in a multidisciplinary work environment
45

Machine Learning Scientist / Senior Scientist Resume Examples & Samples

  • Scientific expertise and applied experience in Machine Learning (ideally, a combination of excellent academic research and high-impact commercial experience)
  • In depth understanding of common Machine Learning algorithms (e.g., for classification, regression and clustering)
  • Track record in advanced topics of Machine Learning (e.g., Bayesian inference, hierarchical models, deep learning, Gaussian processes, causal inference, graph theory, etc.)
  • Advanced programming skills in Python and/or R (and their related data processing, Machine Learning, and visualization libraries)
  • Practical experience in preparing data for Machine Learning (e.g., using SQL and/or NoSQL technologies)
  • Completion of at least one significant project (equivalent of a great PhD research project, and/or a viable commercial product) in applied Machine Learning
  • Integration of Machine Learning algorithms with big-data platforms (e.g., Spark) and high-performance computing ecosystems (e.g., CUDA)
  • Programming in C++, Java
  • Deployment of algorithms as realtime/ highly available services
  • Integration with front-end systems (e.g., HTML5/ native mobile apps)
  • Employing Machine Learning in collaborative commercial settings (e.g., using DevOps methodologies and tools such as GitHub), ideally, in collaboration with product development teams
  • We invest heavily in training you in all aspects of analytics as well as in leading analytical tools and techniques
46

Machine Learning Scientist Resume Examples & Samples

  • Research, design, implement and evaluate novel forecasting models and algorithms in our own forecasting toolbox which meets Amazon's production requirements
  • Work on large-scale datasets, focusing on creating scalable and accurate forecasting systems in versatile application fields
  • Collaborate closely with research team members on developing systems from prototyping to production level
  • Research experience in machine learning and ideally in time series proven by scientific track record
  • Deep understanding of machine learning fundamentals
  • Strong coding skills in two or more programming languages where one is Java, Scala, C/C++ or similar and the other is Python, Julia or similar
47

Machine Learning Scientist Resume Examples & Samples

  • PhD in Computer Science, Statistics or related field
  • Publications in top-tier Machine Learning conferences and journals
  • 3 years recent Java or C++ experience
  • Intermediate Linux/UNIX skills
  • Strong sense of ownership, urgency and drive
  • 2 Post-doc or industry experience
  • Experience with distributed data storage and data processing frameworks
  • Experience with Machine Learning toolboxes and frameworks
  • Experience in online learning, reinforcement learning and/or active learning
48

Machine Learning Scientist Resume Examples & Samples

  • A PhD degree in Computer Science, Machine Learning, Computer Vision, Operational Research, Statistics or related field
  • Familiar with theory and practice of information retrieval, relevance, machine learning, and data mining
  • Familiar with the core undergraduate curriculum of Computer Science
  • Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form
49

Machine Learning Scientist Resume Examples & Samples

  • Scope analytics projects including identifying resources and assets needed, determining analysis approach, conducting analysis, and developing execution plans
  • Partner with technical and non-technical resources across the business to leverage their support and integrate our efforts
  • Pro-actively analyze data to uncover insights that increase business value and impact
  • Hold a point-of-view on the strengths and limitations of statistical models and analyses in various business contexts and is able to evaluate and effectively communicate the uncertainty in the results
50

Machine Learning Scientist Resume Examples & Samples

  • Use statistical and machine learning techniques to create scalable traditional and non-traditional approaches for product recommender systems and search relevancy
  • Analyzing and understanding large amounts of Amazon’s historical business data for personalized product recommendations and search relevancy
  • Design, development and evaluation of highly innovative models for for personalized product recommendations and search relevancy
  • Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
  • PhD/BS/MS degree in with a focus in recommender systems, Machine Learning, or related technical field and 7+ years of related work experience
  • Proficiency in model development, model validation and model implementation
  • Hands on experience programming in R, Java, C#, C++ or other similar programming languages
  • Hands on experience with scripting languages such as Python, Perl
  • Work well in a fast-moving team environment and effectively deliver technical implementations having complex dependencies and requirements
  • Experience in recommender systems, data mining, machine learning, or artificial intelligence in a commercial setting
  • Ability to deal with ambiguity and innovate and simplify
  • Experience in search technologies
  • Experience in search relevancy systems
51

Machine Learning Scientist Resume Examples & Samples

  • Designing, developing and maintaining core system features, services and engines
  • Helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product
  • Working with scientists and other engineers to investigate design approaches, prototype new technology, and evaluate technical feasibility
  • Operating in an Agile/Scrum environment to deliver high quality software against aggressive schedules
  • Bachelor's degree in Electrical Engineering, Computer Science, Mathematics, or related technical field
  • Familiar with programming languages such as C/C++, Java, Perl or Python and open-source technologies (Apache, Hadoop)
  • Experience with OO design and common design pattern
  • Knowledge with data structures, algorithm design, problem solving, and complexity analysis
  • Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences, Mathematics, or related technical field
  • Experience developing cloud software services and an understanding of design for scalability, performance and reliability
  • Experience defining system architectures and exploring technical feasibility trade-offs
  • Experience optimizing for short term execution while planning for long term technical capabilities
  • Ability to prototype and evaluate applications and interaction methodologies
  • Ability to produce code that is fault-tolerant, efficient, and maintainable
  • Academic and/or industry experience with standard AI and ML techniques, NLU and scientific thinking
  • Ability and willingness to multi-task and learn new technologies quickly
  • Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences
52

Machine Learning Scientist Resume Examples & Samples

  • Apply Machine learning techniques on large corpus of documents to refine EBSCO Knowledge Graph
  • Develop novel algorithms in the area of NLP and ML to advance understanding of users context
  • Apply Machine Learning to improve document ranking, linking and summarization capabilities of the platform
  • Collaborate with members of search engineers
  • Analytical skills: Able to structure and process qualitative or quantitative data and draw insightful conclusions from it. Exhibits probing mind and achieves penetrating insights
  • Problem Solver: Applies critical thinking and structured problem solving to address root causes
  • Strategic thinking/visioning: Able to see and communicate the big picture in an inspiring way. Determines opportunities and threats through comprehensive analysis of current and future trends
  • Experience with any of the following technologies: MongoDB, MySQL, DynamoDB
53

Applied Machine Learning Scientist Resume Examples & Samples

  • MS or Ph.D. in Machine Learning or closely related area or equivalent work experience
  • Solid background in statistical learning techniques for NLP (HMMs, CRFs, SVMs, LDA, LSI, MRFs, etc.)
  • Experience implementing ML/NLP algorithms as well as the ability to modify standard algorithms (e.g. changing objectives, working out the math, implementing and scaling)
  • Experience developing prototypes by manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
  • Experience with Object Oriented design and development using any of programming languages Java, Python, Scala, C++
  • Facility with UNIX
54

Machine Learning Scientist Resume Examples & Samples

  • Natural Language Processing,
  • Text Analytics,
  • Machine learning,
  • Semantic Analysis,
  • Entity Classification,
  • Topic Extraction,
  • Parsing
  • Creating structured data from large unstructured datasets
55

Machine Learning Scientist Resume Examples & Samples

  • Publications in top-tier Machine Learning or database conferences and journals
  • 3+ years recent Scala, Java, or C++ experience
  • 2+ years post-doc or industry experience
  • Experience in data cleaning or information integration
  • Experience with distributed data storage systems and data processing frameworks
56

Machine Learning Scientist Resume Examples & Samples

  • Publications in top tier Machine Learning conferences and journals (e.g. NIPS, ICML, AISTATS, UAI, JMLR, TPAMI, JASA, JRSS, Annals of Statistics)
  • 3 years recent Java, C++ or Python experience
  • Expert with practical experience in Object Oriented Design
  • 2 years Post-doc or research experience in industry
  • Experienced in Bayesian Optimization methods
  • 1+ year experience in Scala development
57

Machine Learning Scientist Resume Examples & Samples

  • 3-6 years experience with an OO language (Java, Ruby, Smalltalk, Objective-C, etc) or python etc
  • Excel in Machine learning models, Time series prediction, Deep Learning, Reinforcement Learning
  • Familiar SQL and data analytic skills
  • Can extract data independently and build up machine learning model based on it
  • Good in English, both speaking and writing
  • Major in Computer Science, Mathematics, Engineering or related area. Prefer PhD’s degree
58

Machine Learning Scientist Resume Examples & Samples

  • Prototype these models by using high-level modeling languages such as MATLAB or R, or in software languages such as Python. A software team will be working with you to transform prototypes into production
  • Ph.D. in Machine Learning, Data Mining, Statistics, Applied Mathematics, or a related field AND 2 or more years of industry experience, OR a Master’s degree in Machine Learning, Data Mining, Statistics, Applied Mathematics or a related field AND 4 or more years of industry experience
  • 4+ years of experience in machine learning with domain knowledge and experience in the following areas: data-driven statistical modeling, discriminative methods, feature extraction and analysis, supervised learning
  • Distributed programming experience is highly recommended
59

Machine Learning Scientist Resume Examples & Samples

  • Algorithm engineering for our machine learning group
  • Taking academic work and applying it to our customer’s problems
  • Keeping up to date with developments in academia
  • Grow with the company and expand your role alongside fulfilling existing needs
  • Experience using, modifying, and designing convolutional neural networks
  • Experience with Deep learning libraries (preferably Tensorflow but also Torch and Caffe)
  • Proficiency in C++ and Python
  • Computer vision libraries, e.g. OpenCV
  • Deploying algorithms in distributed / cloud computing
  • Designing high performance, resilient implementations
  • Porting algorithms to other architectures e.g. ARM
  • Implementing algorithms on heterogeneous systems (e.g. GPU, DSP, FPGA)
60

Senior Data & Machine Learning Scientist Resume Examples & Samples

  • Ability to find, source, and store unique data sets that may be useful for analysis (e.g. go get Google Analytics data and add it to your model)
  • Ability to explore and implement advanced technological solutions such as machine learning
  • SPSS
  • Hadoop (HBase, Hive, Pig, RHadoop)
  • AWS (RedShift, Kinesis, EMR)
61

Machine Learning Scientist Resume Examples & Samples

  • B.S. degree in Computer Science or IT related discipline
  • 2+ years of machine learning experience
  • 2+ years’ experience in design and problem solving
  • 2+ years of Experience in one or more of the commonly used parallel/distributed systems/technologies (Apache Hadoop, Apache Spark, MPI, CUDA, Hive, Java, C++, C#)
  • 1+ Publications in major conferences and/or journals
  • Intense curiosity and willingness to question
  • Have a deep desire to work collaboratively, solve problems with groups, find win/win solutions and celebrate successes
  • Strong bias for architecting for performance, scalability, usability, security, and reliability
  • Good communicator with the ability to analyze and clearly articulate complex issues and technologies understandably and engagingly
62

Robotics & Machine Learning Scientist Resume Examples & Samples

  • A Ph.D in CS Computer Vision, Machine Learning, Statistics, or in a highly quantitative field
  • 4+ years of relevant research experience in planning algorithms and
  • 3+ years of industry experience in robotic
  • Experience implementing control systems
  • Experience with computer vision and machine learning systems
63

Machine Learning Scientist Resume Examples & Samples

  • Practical experience in applying fundamental machine learning algorithms to solve complex problems
  • Experience with modifying standard algorithms (e.g. changing objectives, working-out the math, implementing and scaling)
  • 3+ years in one or more major programming languages (Python, Java, C++, C, Perl/Ruby, etc.)
  • At least 1 year of industry or postdoctoral experience with machine learning
  • Previous experience solving business problems through machine learning, data mining and statistical algorithms in a fast paced environment
  • Experience in building production quality and large scale deployment of applications related to machine learning
  • Experience with developing prototypes by manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
  • Experience in the real-time processing of high-velocity time series data
  • Experience working with big data and relevant techniques, e.g. unsupervised learning
  • Excellent written and verbal communication skills, and the ability to clearly articulate rigorous technical concepts and considerations to non-experts
  • Experience with sequential data modelling, time-series analysis, signal decomposition, deep learning, and multi-modal learning algorithms
  • Track-record of novel algorithm development, e.g. publications in one or more of the following: KDD, NIPS, SIGIR, ICML, etc
  • Ability to work both independently on ambiguous problems and in highly collaborative team environments