Learning Scientist Resume Samples

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KM
K Monahan
Katheryn
Monahan
2950 McGlynn Knoll
Philadelphia
PA
+1 (555) 160 6910
2950 McGlynn Knoll
Philadelphia
PA
Phone
p +1 (555) 160 6910
Experience Experience
Philadelphia, PA
Learning Scientist
Philadelphia, PA
Schroeder Inc
Philadelphia, PA
Learning Scientist
  • Developing a research synthesis and product design rationale (20%)
  • Conducting both agile and sophisticated learner research to substantiate learning theories (20%)
  • Using learning science research to support product evaluation, implementation, and marketing (20%)
  • Partnering with the VP, Applied Learning Sciences to build collective consciousness and organizational capacity around the learning sciences (20%)
  • Partnering with the VP, Applied Learning Sciences in seeking thought leadership in the learning sciences (20%)
  • Participate in the formulation of a defensible set of frameworks, research syntheses, design principles, and white papers addressing aspects of the learning sciences and their application to digital learning products
  • Design learning science briefs for each product category that articulate the instructional model, assessment strategy, approach to personalization, and learner self-efficacy strategies
Detroit, MI
Machine Learning Data Scientist
Detroit, MI
Abshire, Champlin and Schimmel
Detroit, MI
Machine Learning Data Scientist
  • Work with very large data sets (both structured and unstructured) and design, develop and implement R&D and pre-product prototype solutions
  • Provide thought-leadership and oversee execution of diverse projects
  • Proficient in software design and development including Data Structure, OOP/OOD, SQL/NoSQL Database
  • Identify emergent trends and opportunities for future business growth and development
  • Design and develop algorithms and define path to implementation with IT teams
  • Perform Data cleansing/transformation, feature engineering, apply statistical analysis, data visualization, data mining
  • Monitor data quality and identify data integrity problems
present
Chicago, IL
Machine Learning Research Scientist
Chicago, IL
Reynolds-Casper
present
Chicago, IL
Machine Learning Research Scientist
present
  • Creativity / innovation – Possessing curiosity and a passion for driving continuous improvement through spotting opportunities and seeking the views of others
  • Advancing the state of the art in areas such as natural language processing, computer vision, sensor fusion, object tracking, and motion planning
  • Identifying key machine learning technologies, and determining how they’ll impact ARM products and partners
  • MS or PhD in computer science, mathematics, physics, electrical engineering, machine learning or equivalent
  • Attending conferences and collaborating with academic partners
  • Reporting and presenting experimental results and research to internal and external partners
  • Proven knowledge of machine learning/deep learning
Education Education
Bachelor’s Degree in Computer Science
Bachelor’s Degree in Computer Science
West Virginia University
Bachelor’s Degree in Computer Science
Skills Skills
  • If you're eager, dynamic and ultimately a good fit, you'll be afforded the opportunity to change the future of education
  • Strong understanding of how learning science literature affects learning architecture, learner experience design, and learner outcomes
  • Using learning science research to support product evaluation, implementation, and marketing (20%)
  • Partnering with the VP, Applied Learning Sciences to build collective consciousness and organizational capacity around the learning sciences (20%)
  • Partnering with the VP, Applied Learning Sciences in seeking thought leadership in the learning sciences (20%)
  • Fluency in learning theories, design-based research, formative evaluation methods, and third-party validation techniques
  • Conducting both agile and sophisticated learner research to substantiate learning theories (20%)
  • Expertise working with subject matter experts, product management, UI designers, and engineers
  • Expertise with user testing methodologies
  • If you're interested in this position, submit your resume
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15 Learning Scientist resume templates

1

Research Scientist Digital Learning & Assessment Resume Examples & Samples

  • Demonstrate excellent communication skills, (oral, written, and business), necessary to function effectively as a primary contact with internal project teams and stakeholders
  • Provide consultative training in the effective use of education data to help guide policy, programs, and instructional practice
  • Communicate about advanced technical issues in learning and assessment and modeling
  • Present technical information to a variety audiences in ways they can understand
  • Present at national and/or international conferences
  • Manage communication effectively in distributed teams using electronic/cloud-based tools
  • PhD or other doctoral degree preferred, with a focus in one of the following areas: learning science, cognitive science, educational psychology, educational technology, instructional systems design, or related discipline
  • 3-5 years relevant work experience is preferred
2

Learning Scientist Resume Examples & Samples

  • Learner-Centered Design and Evaluation
  • Academic Design Training, Guidance, and Communication
  • Developing a research synthesis and product design rationale (20%)
  • Conducting both agile and sophisticated learner research to substantiate learning theories (20%)
  • Using learning science research to support product evaluation, implementation, and marketing (20%)
  • Partnering with the VP, Applied Learning Sciences to build collective consciousness and organizational capacity around the learning sciences (20%)
  • Partnering with the VP, Applied Learning Sciences in seeking thought leadership in the learning sciences (20%)
  • Design learning science briefs for each product category that articulate the instructional model, assessment strategy, approach to personalization, and learner self-efficacy strategies
  • Validate the application of learning theories to product design at early, formative stages of development using user-centered design and design-based research techniques, both independently and in partnership with institutions and learning labs
  • Advanced degree in Instructional Design, Educational Technology, Educational Psychology, or related field
  • Minimum of 3 years leading the research-based design of technology, software, or digital learning products
  • Strong understanding of how learning science literature affects learning architecture, learner experience design, and learner outcomes
  • Expertise working with subject matter experts, product management, UI designers, and engineers
  • Expertise translating research into software requirements
  • Classroom teaching experience preferred
3

Automated Driving Research Scientist CV & Machine Learning Resume Examples & Samples

  • Design, train and evaluate various machine learning systems for use in object detection and semantic scene understanding
  • Ph.D. in Engineering, Natural Sciences (Math, Physics, Chemistry etc.)
  • 3+ months hands-on experience in Deep Learning or Machine Learning
  • 1+ years of experience in multiple contemporary computer programming languages, e.g., C/C++, PERL, Python, Java, OpenGL, MATLAB/Stateflow/Simulink, etc
  • Experience with algorithms such as motion control, image processing, simultaneous localization and mapping, geospatial location, rendering 3D data, computer graphics, etc
  • Familiarity with existing deep learning libraries (e.g. Torch, Theano, Caffe, PyBrain, Neon, etc.)
  • Experience with sensing systems such as cameras, radar, lidar, GPS, IMUs, etc
  • Experience with system requirements, testing, validation, software release
  • Passion to develop and expand deep learning technologies
  • Present results for internal management and at external venues such as conferences
4

R&D Data Scientist Deep Learning Resume Examples & Samples

  • Research and apply the latest quantitative techniques toward the solution of important business problems
  • Review academic / industry literature, develop and test models, and gain insights from research findings
  • Translate ideas and theory into actionable solutions to real business problems
  • Identify new methodology and novel data sources and explore their potential use in developing business insights
  • Explore emerging technologies and analytic solutions for use in quantitative model development
  • Help maintain and enhance existing models
  • Master’s degree in a quantitative field such as Computer Science, Statistics, Economics, Mathematics, Physics, Operations Research, Cognitive Neuroscience, or Quantitative Finance
  • 3+ years of experience involving complex quantitative modeling and analysis in a business or academic setting, as indicated by relevant work experience and / or academic research and publications
  • 2+ years of project experience in deep learning, such as Convolutional neural networks, Autoencoder, and Restricted Boltzmann machines
  • 2+ years in Python and other deep learning software packages (Caffe, Theano, Tensorflow)
  • 2+ years of experience in at least two of the following languages: R, MATLAB, Java, C/C++/C#, SAS
  • Ph.D. in a quantitative field such as Computer Science, Statistics, Economics, Mathematics, Physics, Operations Research, Cognitive Neuroscience, Quantitative Social Science, Quantitative Finance, etc
  • Demonstrated skills in manipulation and data mining / pattern recognition of large structured and unstructured data sets
  • Experience with big data technologies such as Spark, Hadoop, Map/Reduce, Hive, etc
  • Experience with parallel / grid / GPU computing
  • Ability and desire to quickly adapt to changing business objectives; ability and desire to quickly learn and apply new quantitative techniques and analytics technologies
  • Experience with advanced econometrics / statistics (Bayesian methods) / time series analysis / forecasting / causal inference
  • Experience with optimization techniques, e.g. linear / nonlinear programming, dynamic / stochastic programming, optimal control, etc
  • Experience with quantitative finance, Monte Carlo simulation, risk quantification, portfolio optimization, economic scenario generation, etc
  • Experience with theoretical / empirical techniques commonly used in industrial organization, e.g. game theory, mechanism design, etc
5

Reinforcement Learning Research Scientist Resume Examples & Samples

  • PhD in computer science, statistics, data science, operations research, or other related areas
  • Knowledge of distributed programming in MPP environment using MPI and multi-threading
  • Experience writing large, complex programs in C or similar programming language
  • Background in machine learning and/or data mining
  • Understanding of the Reinforcement Learning problem such as the agent-environment interface, the goals and rewards
6

Data Scientist With ML Background for Machine Learning Development Resume Examples & Samples

  • Closely work with customers, partners and internal teams to enhance the solution and systems, troubleshooting data issues etc
  • Learn quickly new mathematical or technical methods
  • Implement most recent algorithms and approaches for machine learning in collaboration with our data scientists and researchers
  • Demonstrates up-to-date expertise in Software Engineering and applies this to the development, execution, and improvement of action plans
  • Initiates and participates in projects in the area of prediction, optimization, and processes using advanced statistical / mathematical approaches, in the enterprise environment
  • Design best architecture and select the most appropriate modeling techniques and data visualization for big data analysis
  • Experience in hands-on software development
  • Iteratively test, refine and improve the models
  • M.S. or Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Math or related topics
  • Strong background in mathematics, statistics and programming
  • Experience in statistical modeling, machine learning, or data mining practice
  • Experience in SQL, relational databases, database concepts, dimensional modeling and database design
  • Proficient in one or more programming languages such as Java, C++, Python, JavaScript
  • Familiar with one or more machine learning or statistical modeling tools
  • Experience with cloud-based SaaS applications and security
  • Strong Industry domain knowledge and experience preferred
  • Knowledge in Natural Language Processing preferred
7

Machine Learning Research Scientist Resume Examples & Samples

  • U.S. Citizenship (This is an absolute requirement, no exceptions. This is required due to requirements imposed by contracts with the Federal government.)
  • M.S. or Ph.D. degree in a field related to machine learning (Computer Science, Statistics, Mathematics, or related field)
  • 5-10 years of work experience in a relevant field
  • Hands-on skills in implementation of machine learning techniques and development of software systems that incorporate machine learning
  • Ability to apply machine learning to real-world problems, such as cyber security, IP networking, target recognition, video analytics, social network analysis, or other relevant areas
  • Effective communication and writing skills
  • Experience in working on Government proposals, especially DARPA proposals
  • Experience in working on DARPA, IARPA, ARL, AFRL, or similar agency programs
  • Experience with leading teams of people in technical projects related to machine learning and data analytics
8

Machine Learning Data Scientist Resume Examples & Samples

  • Conduct Big Data Research
  • Creatively source, aggregate and analyze massive amounts of data
  • Use SQL to query large databases
  • Monitor data quality and identify data integrity problems
  • Use Machine Learning applications on unstructured data to extract investment insights
  • Use Business Intelligence applications to identify investment signals and trends
9

Data Scientist Generative Design Deep Learning Resume Examples & Samples

  • PhD in Computer Science, Applied Mathematics, Electrical Engineering, Operations Research or Statistics
  • Demonstrable research and innovation track record as an intern or graduate assistant (publications, research monographs etc.)
  • Proven Java or C++ development skills a must
  • Experience in solving Machine Learning problems using Deep Learning
  • Familiarity with MapReduce, Hadoop or Mahout and knowledge of Rule Engines
  • Passion and drive for a career in software development
  • 3+ years of big data analytics experience in a research & development environment
  • Exposure to configuration management (versioning control, continuous integration, Apache Maven)
  • Full-text search (Apache Lucene or similar), or database full-text search
  • Knowledge of various open-source Frameworks
  • Knowledge of big data frameworks
10

Data Scientist Generative Design Deep Learning Resume Examples & Samples

  • Lead the research activities focused at applying combination of Deep Learning and Knowledge Representation pipelines to design, analysis and engineering workflows for real world problems
  • Research, design, and implement algorithms that power knowledge inference and online recommendations, based on Deep Learning, to consume design and engineering data in real-time
  • Dive into huge, noisy, and complex real-world behavioral data to produce innovative analysis and new types of predictive models of engineering behaviors and manufacturing processes performance
  • PhD required in Machine Learning or related field
  • 7+ plus years of related experience
  • Hands-on coding skills and ability to quickly prototype in C++ is a must. Further experience in one or more of following: R, WEKA, Pandas, Octave, Matlab, Python, Java, JavaScript
11

Machine Learning Research Scientist Resume Examples & Samples

  • Graduate-level research experience in one of the areas described above
  • Using standard machine learning and/or NLP toolkits
  • Proficiency in modern programming and scripting languages, such as Java, Scala, C++, or Python
  • Proficiency in relevant statistical mathematics
  • Ability to develop novel ML and/or NLP techniques and to apply them to real-world problems faced by Oracle's product groups and customers
  • Applying existing machine learning and natural language processing techniques and technologies to real-world problems
  • Database technologies such as Oracle and MySQL
  • Big Data platforms such as Hadoop, Spark, or MPI
  • Familiarity with special-purpose computing architectures as applied to machine learning
12

Senior Deep Learning Scientist Speech Resume Examples & Samples

  • Staying up to date with latest Speech/NLP research and applications to share internally
  • Mentoring Data Scientists and Data Engineers on Speech/NLP problems
  • Provide consulting to Analytic Solutions team to build Speech/NLP packaged solutions and offerings
  • Building Speech/NLP solutions with tools such as Torch, TensorFlow, MXNet et al
  • Hands on experience building and deploying chatbots a plus
  • Linguistics knowledge and understanding
  • Knowledge of recent research in speech and NLP
  • Python and Linux command line skills
  • Experience with at least one deep learning library (TensorFlow, Torch, MXNet, Theano, etc.)
  • 6+ years working in Speech/NLP Research or Implementation
  • Professional consulting experience a plus
13

Automated Driving Research Scientist Machine Perception & Learning Resume Examples & Samples

  • Design, prototype, and evaluate effective and efficient sensor feature detection, tracking, mapping and localization algorithms and systems, including computer vision algorithms
  • Design, prototype, train and evaluate various machine learning methods for use in detection, classification and regression tasks, significantly improving performance or reducing cost
  • Develop, evaluate and compare deep learning algorithms for specific applications and tasks to improve performance, data collection, training, and suitability for embedded applications
  • Publish/present technical reports, papers and/or pursue Intellectual Property rights
  • Master’s degree in Engineering, Computer Science, Natural Sciences, Robotics, or Statistics
  • 1+ years of experience in multiple contemporary computer programming languages, e.g., C/C++, Python, Java, OpenGL, PERL, MATLAB/Simulink, software libraries and tools
  • Ph.D. in Engineering, Computer Science, Natural Sciences, Robotics, Statistics or related field
  • 5+ years of Computer Vision and/or Machine Learning hands on work experience
  • Expert experience in designing and building state of the art feature detectors and trackers
  • Experience with algorithms such as statistical signal processing, image processing, simultaneous localization and mapping, geospatial location, rendering 3D data, computer graphics, etc
  • Experience developing and optimizing algorithms and systems with reduced computational complexity or cost
  • Experience in multiple computer hardware, operating systems and tools, e.g., embedded microcontrollers, GPUs; Windows, UNIX, Linux; git, Make, subversion, glibc, gcc, bash, etc
  • Experience with the CUDA platform
14

HP Labs Machine Learning Research Scientist Resume Examples & Samples

  • Broad knowledge of machine learning, statistical modeling, or data mining research
  • Expertise with building systems based on machine learning techniques
  • Experience with one or more deep learning frameworks such as Theano, Tensorflow, or Torch
  • Prototyping skills in C++, Python, Java, or Matlab
15

iXp Intern, Machine Learning Data Scientist Resume Examples & Samples

  • Requires candidates to currently be enrolled in a Masters or PhD degree program which is applicable to the position
  • Fluency in Java, Python, or other related programming languages
  • Publications or demonstrated experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science
  • Experience building systems based on machine learning and/or deep learning methods
  • Candidates must be located in the Silicon Valley to be considered
  • Must be able to work onsite in Palo Alto, CA during summer 2017
16

Deep Learning & AI Data Scientist Resume Examples & Samples

  • AA / AS degree in Computer Science, Statistics, Mathematics or related
  • BA / BS degree (Computer Science, Statistics, Mathematics related
  • MA /MS degree (Computer Science, Statistics, Mathematics related
  • 5+ years knowledge in conducting statistical analytics (statistical
  • 5+ years in developing parallel code and in Big data self learning
17

Automated Driving Research Scientist Machine Vision & Learning Resume Examples & Samples

  • Participate in technical discussions and collaborate in the creation of new ideas for automotive applications within the existing autonomous vehicle research team; coordinate with engineers in related Ford R&D teams; contribute to technical roadmap for future development
  • Maintain close contact to the scientific and industrial community in computer vision and machine learning, and perform scouting and assessment of new approaches
  • Ph.D. in Engineering, Computer Science, Natural Sciences, Robotics, or Statistics
  • 1+ years of experience in multiple contemporary computer programming languages, e.g., C/C++, Python, Java, OpenGL, PERL, MATLAB/Simulink, and software libraries and tools
  • Demonstrated ability to carry out independent research and lead projects
  • Experience with computer vision, machine learning, DNNs, and numerical optimization
  • Passion to develop and extend deep learning technologies
  • Knowledge of 3D co-ordinate frames and transformations, vector mathematics, matrix algebra, state estimation, probabilistic inference and modeling, etc
  • Experience presenting results to internal management & at external venues such as conferences
18

Maching Learning Scientist Resume Examples & Samples

  • Fundamental ML knowledge: You either have authored papers in relevant top-tier venues (like ICML, NIPS, KDD, CVPR, ACL, etc.) and/or have read them for pleasure
  • Excellent development and implementation skills: You enjoy creating efficient, well-designed implementations of learning algorithms, finding their non-trivial applications, and conducting thorough evaluations
  • Drive to democratize ML: You are both amazed by and proud of the machine learning community and its accomplishments and at the same time disappointed by its localized impact thus far. You want to help make machine learning useful beyond the web companies across a wide array of application domains
19

Data Scientist With Machine Learning Experience Resume Examples & Samples

  • Recommend next steps to ensure successful project completion and to help team penetrate client accounts
  • Provide support in the development of solutions and preparation of RFP responses
  • Medical device company
  • Pharmacy (corporate)
  • Financial company investing in the Life Sciences such as Venture Capital or Investment Bank
20

Data Scientist for Deep Learning Center of Excellence Resume Examples & Samples

  • Contribute to building deep learning models solving our customers’ toughest problems
  • Familiarity with recent advances in deep learning (convolutional neural networks, recurrent neural networks, reinforcement learning, generative adversarial networks, memory networks etc.)
  • Good written and oral communication skills in English; German a plus
  • Hands-on experience building models in one or multiple data domains (natural language, image, video, speech, tabular)
  • 0-4 years of professional experience. Graduates are also welcome to apply
21

Data Scientist for Machine Learning for Sales & Services Resume Examples & Samples

  • Build deep learning models solving our customers’ toughest problems
  • B.S., M.S. or PhD in Computer Science or a related field
  • 0-2 years of professional experience
22

Machine Learning Research Scientist Resume Examples & Samples

  • Identify key machine learning technologies and algorithms, and determine how they’ll impact ARM products and partners
  • Interface with product teams to develop new IP and microarchitectures
  • Report and present experimental results and research findings clearly and efficiently
  • MS or PhD in computer science, mathematics, physics, electrical engineering, machine learning or equivalent
  • Proven knowledge of machine learning/deep learning
  • Good understanding of CPU and GPU microarchitecture
  • Strong GPU/CPU programming skills
  • Scientific, data-driven, objective mindset
23

Machine Learning / Data Scientist Strategist Resume Examples & Samples

  • Create a vision and develops strategy/technology roadmaps for Big Data Machine Learning research, engineering and technology development and transfer across the Global Business Units and company at large
  • Communicates strategy and technology roadmaps to executive staff and key industry partners and customers; leverages recognized technical and business expertise to influence, guide, and shape business strategy and decision-making at the highest organizational levels
  • Provides consultation, design input, and feedback for research and new product development and design reviews across multiple organizations and architectures
  • Represents the company as a recognized technology and research expert at key industry and scientific conferences and meetings; prepares and delivers literature and presentations for publication and peer review; creates patent applications and supporting documentation
  • Evaluates and develops external relationships for technologies and innovations for alignment with research roadmap and potential business value; creates strategic plan for integration and update into research and product architecture
  • Guides and mentors less-experienced staff members to set an example of product engineering innovation and excellence
  • Participates in and provides input on process for selection of future technical leaders
  • Bachelor's, Master's or PHD degree in Computer Science, Machine Learning, Mathematics, Engineering or similar level of applied research knowledge equivalent
  • Typically 15+ years experience, including graduate or postgraduate research
  • Industry expert regarding scientific and technology research and development of methodologies, tools, standards, protocols, and investigations. Awareness of the leading edge Big Data trends, approaches, and success models
  • Understanding of distributed computing allowing for creation of architectures that are scalable and responsive to the ‘near real time’ demands for information. History of working with large data sets and high transaction rates. Amazon cloud services of Databricks, S3, Redshift, etc. is a must
  • History of innovation with multiple examples of developing and transferring industry- leading technologies and practices into product designs
  • Integrating research innovations and technologies produced into the overall research, company and product architecture
  • Excellent written and verbal communication skills; mastery in English and local language
  • Ability to effectively communicate research architectures, plans, proposals, and results, and negotiate options at the most senior organizational levels
24

Deep Learning Research Scientist Resume Examples & Samples

  • PhD with at least 2 years of experience in Computer Science or other engineering discipline with focus on Deep Learning and feature discovery
  • In depth knowledge and working experience on the various aspects of training and deployment of deep networks
  • Strong understanding of machine learning algorithms & principles
  • Familiarity with DL frameworks such as TensorFlow, Theano or Torch and strong experience in at least one of those
  • Solid background in numerical optimization
  • Proven programming skills, in at least one of the following languages: C, C++, Python, Java, Scala
  • Strong publication record (e.g. NIPS, ICML, AAAI, ICLR, KDD) required
  • Knowledge of Linux
  • Experience working with GPUs is desired
  • Excellent communication skills and a proven ability to multitask and deliver on development tasks
  • Resume/ CV
  • A recent publication or statement of past experiences
25

Deep Learning Research Scientist Resume Examples & Samples

  • Develop SAS Deep Learning (DL) toolkit on the state-of-art SAS Viya platform
  • Implement various SAS DL architectures and algorithms on SMP, MPP, and GPUs for computer visions, natural language processing, speech recognitions, etc
  • Research and apply Reinforcement Learning, Transfer Learning, and Generative Adversarial Networks for various domains such as fraud, cyber security, recommender systems and so on
  • Discuss, propose, and implement new ideas and applications within the SAS DL team
  • Master’s degree or Ph.D. in Computer Science, Mathematics, Statistics, or Physics (Machine Learning or Deep Learning is a plus)
  • Proven programming skills such as Python, C, or C++
  • Experience with GPU computing (CUDA, OpenCL) and HPC (MPI, OpenMP)
  • Strong experience with DL frameworks such as Caffe, Theano, Torch, CNTK, MXNet, or TensorFlow
  • Strong mathematical skills in machine learning and deep learning
  • Strong ability for teamwork and motivation for collaborations and good communication and organizational skills
26

Machine Learning Data Scientist Resume Examples & Samples

  • Ability to work as part of a team and to communicate effectively
  • Demonstrated experience communicating complex findings in a clear and concise manor to divisional management
  • Demonstrated experience developing and managing complex projects
  • Demonstrated experience formulating, approaching, and solving complex analytical problems using a quantitative, scientific approach
  • Demonstrated experience in machine learning, predictive modeling, or statistics / data mining using large amounts of structured, semi structured, and unstructured data
  • Demonstrated experience using analytically oriented languages such as R, Julia, Python, or Matlab
  • Demonstrated experience working with large, complex datasets using big data technologies and languages such as the Hadoop ecosystem and Python, Java, or Scala
27

Artificial Intelligence & Machine Learning Research Scientist Resume Examples & Samples

  • Work as an independent yet integral member of a team to develop innovative and creative AI / ML solutions for highly automated vehicles with world leading experts of autonomous vehicles
  • Develop and maintain high quality C/C++ and Python code under Linux for general purpose PCs and embedded hardware platforms. Test and debug software on autonomous research vehicle prototypes
  • Plan and execute complex and challenging technical projects
  • Possess strong interpersonal skills and consistently demonstrate ability to work in a team environment and with cross-functional global teams
  • Maintain state-of-the-art technical expertise in artificial intelligence, machine learning and software programming. Generate intellectual property
  • PhD with 2+ years or Masters with 5+ years of experience in computer science, electrical engineering, mathematics, physics
  • Expert-level knowledge in learning algorithms such as inverse reinforcement learning, deep reinforcement learning and probabilistic inference for decision support systems
  • Knowledge and hands-on expertise in deep neural network topologies such as convolutional nets, recurrent nets, RBMs, causal reasoning, probabilistic programming
  • Strong software development skills in C/C++ under Linux environments with a proven ability to deliver high quality software coding on time
  • Mathematically minded with experience in manipulating high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships and trends with machine learning techniques
  • Develop requirements and evaluation methods for artificial intelligence technologies and benchmark vendor technologies
  • Experience in algorithm development, prototype system development and prototype software implementation on hardware platforms
  • Everything you need to develop your skills and realize your career goals
  • An environment which encourages a balance between work and personal life
  • A culture where collaboration and team work is fostered
  • A competitive total compensation package
  • A comprehensive benefit and retirement savings program to protect you and your family
  • The resources and support you need for your health and well-being
  • A company that is committed to supporting organizations and programs focused on safety, STEM education, community development, and environment & energy
28

Deep Learning Scientist Resume Examples & Samples

  • 1) Employ the best of Deep Learning research for solving business problems; disrupting the current practice in insurance
  • 2) Build and refine Deep Learning algorithms that can find “useful” patterns in large multi-modal data (particularly, images, text, conversations, and transactional data)
  • 3) Provide the business with new product ideas, as well as data-driven apps, insights and strategies
  • 4) Participate in, lead, and create cross-functional projects
  • 5) Communicate (both oral and written) with colleagues and stakeholders (both internal and external)
  • 1) Completion of one significant project (equivalent of a PhD research project, and/or a viable commercial product) in one or more of the hiring themes
  • 2) Scientific expertise, strong track record, and real-world experience in Deep Learning, especially with hands-on experience in hyper-parameter tuning and deep construction / distribution (e.g., architecture design in DNN/CNN/RNN, parameter initialization, activation, normalization, and optimisation)
  • 3) Strong background in machine learning and statistical modeling (e.g., classification, regression, and clustering)
  • 4) Expertise in programming (e.g., Python and C++) and computing technologies (high-performance computing, e.g., CUDA)
  • 5) Ability to use existing machine/deep learning libraries (e.g., TensorFlow, Torch, Theano, Caffe, and scikit-learn)
  • 1) Track record in integrating machine learning with real-time computing (including mobile apps and front-end systems)
  • 2) Experience in employing machine learning in a commercial setting – in collaboration with product development teams
  • 3) Publication record in (and willingness to represent AIG in) scientific conferences such as NIPS, CVPR, ICML, ICCV, ECCV, ICLR, and IJCV
  • 4) Broad knowledge of machine learning (including topics such as graph theory, hierarchical modeling, and Bayesian inference)
  • 5) Practical experience of modern big-data computing ecosystems (e.g., Apache Spark)
29

Machine Learning Research Scientist Resume Examples & Samples

  • Identifying key machine learning technologies, and determining how they’ll impact ARM products and partners
  • Developing and adapting machine learning algorithms for energy constrained mobile and wearable devices
  • Interfacing with ARM product teams to influence new hardware and software IP
  • Advancing the state of the art in areas such as natural language processing, computer vision, sensor fusion, object tracking, and motion planning
  • Prototyping hardware and software solutions
  • Attending conferences and collaborating with academic partners
  • Reporting and presenting experimental results and research to internal and external partners
  • BSc, MS or PhD in computer science, mathematics, physics, electrical engineering or related field
  • Proven understanding of machine learning/deep learning
  • Strong CPU/GPU programming skills
  • Some familiarity with computer architecture and hardware design is desirable
30

Machine Learning Data Scientist Internship Resume Examples & Samples

  • Experience on developing production level code on one or more of the following areas: statistical modeling, machine learning algorithms, data pipelines
  • Experience in data science projects, especially experience in scala, R and python
  • Experience in communicating complex scientific results to a general audience using visualization tools
  • Prototyping simple machine learning pipelines to quickly decide if an idea is promising or not, all the way from getting the data to measure model’s accuracy -1 year
31

Research Scientist Bayesian Machine Learning Resume Examples & Samples

  • Develop and apply machine learning and data analytics techniques to support various aspects of an autonomous drilling system (monitoring, diagnosis, control, and planning)
  • Test and validate solutions through simulations and full-scale experiments
  • Keep up to date and expand your knowledge in the field
  • PhD degree in mathematics, physics or computer science with elements of machine learning and data analytics
  • Understanding of various machine learning techniques, such as Gaussian processes, reinforcement learning, and Bayesian approaches
  • Preferred experience in one or more of the following: combination of machine learning techniques with physics-based models, application to control or diagnosis, explicit handling of uncertainty
  • Experience in application to real-world problems
32

Machine Learning Systems Scientist Resume Examples & Samples

  • Design and implementation of novel Machine Learning platforms to support ML application teams
  • Working closely with software engineering teams to drive model implementations and new feature creations
  • Research and implement novel machine learning systems and statistical approaches
  • BASIC QUALIFICATIONS
  • 5 years of PhD in CS Machine Learning or Distributed Systems
  • Skills with Java, Scala or C++ (or other high-level programming language) as well as Python (or similar scripting language)
  • Experience with at least one distributed processing framework, e.g. Spark, Hadoop or MPI
  • 10 years of PhD in CS Machine Learning, Data Management or Distributed Systems
  • 5+ years of hands-on experience in building and operating real-world Machine Learning applications
  • Experience with Scala, Spark, MXNet/Tensorflow
33

Data Science & Machine Learning Research Scientist Resume Examples & Samples

  • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities
  • Conduct experimental analysis efforts using state-of-the-art Machine Learning algorithms
  • Contribute to research efforts in Machine Learning to enable development of new state-of-the-art algorithms for Laboratory problem domains
  • Participate in interactions with inter-organizational contacts and/or external customers
  • Assist in representing the organization by providing input on technical issues for specific projects including preparing and presenting technical reports
  • Bachelor’s (BS) degree in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, Physics, or a related field or the equivalent combination of education and related experience
  • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, unsupervised feature learning, reinforcement learning, zero- or few-shot learning, multimodal learning, natural language processing, ensemble methods, scalable density estimation, scalable online inference, and probabilistic graphical models
  • Fundamental knowledge of and/or experience in Machine Learning including experience in algorithm development
  • Fundamental verbal and written communication skills necessary to effectively collaborate in a team environment to learn and explain technical information
  • Experience in the broad application of one or more higher-level programming languages such as C/C++, Java/Scala, or Python
  • Experience with one or more scientific analysis and prototyping environments such as R, MATLAB, or the SciPy Stack
34

Research Scientist, Alexa Machine Learning Resume Examples & Samples

  • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters
  • Build reporting tools to provide insights and metrics which track trends and explain variance
  • Collaborate with software developers and business leaders to define product requirements, provide analytical support, consultation and communicate feedback
  • 3+ years relevant experience in statistical or predictive modeling and analysis
  • Experience in using R, Python, SAS, Matlab or other statistical/machine learning software
  • Knowledge and experience of SQL (Oracle, MySQL, or PostgreSQL) and AWS RedShift
  • PREFERRED QUALIFICATIONS
  • PhD in Engineering, Mathematics, Economics, Statistics or related field
  • Previous experience in a Machine Learning or data scientist role with a large technology company
  • Excellent communication, analytical and collaborative problem-solving skills
35

Machine Learning & Optimization Data Scientist Resume Examples & Samples

  • Demonstrated experience extracting, cleansing, combining and manipulating large, and diverse data sources for analysis
  • Demonstrated experience in managing and leading large complex projects related to analytics
  • Demonstrated experience performing advanced statistical analysis, including generalized linear models, decision trees, neural networks, etc., to discover business insights and develop predictive models
  • Masters or PhD in Computer Science, AI, Engineering, Statistics, Mathematics, Operations Research, or other relevant scientific field
  • Solid understanding of Machine Learning and Pattern Recognition (mathematical modeling, probability and statistics, and of design and simulation of stochastic systems)
  • Deep understanding and experience building models with Machine Learning and optimization methods such as: Linear/Non-Linear/Integer programming, Deep Learning, Random Forests, Hidden Markov Models, SVMs, Regression, MLE, Time series Analysis, Signal Processing, etc
  • Excellent communication skills with the ability to present complex ideas in a clear and concise manner to a variety of audiences
36

Machine Learning / Data Fusion Scientist Resume Examples & Samples

  • 5+ years of experience with developing software in object-oriented and scripting languages, including Matlab, C/C++, or Python
  • Experience with data fusion, machine learning, signal and imaging processing, algorithm development, and computer vision
  • Experience with research, including developing, designing, and executing research plans
  • Experience with Computer Vision and Machine Learning software packages, including OpenCV, DLIB, Caffe, TensorFlow
  • Experience with GPU programming, including NVIDIA CUDA
  • Experience with integrating commercial software tools for custom application development
  • Experience with biometrics preferred
  • Possession of excellent written and oral communications skills
  • Possession of excellent entrepreneurial thinking, innovation, and real-world problem solving skills
  • PhD degree in an Engineering or Science field preferred
37

Machine Learning Data Scientist Resume Examples & Samples

  • Liaise with key stakeholders in understanding and identifying the business requirements and needs
  • Developing and implementing advanced analytics approaches including statistical modelling, machine learning algorithms, text mining, web analytics etc. to answer business questions and drive actionable insights
  • Work with very large data sets (both structured and unstructured) and design, develop and implement R&D and pre-product prototype solutions
  • Perform Data cleansing/transformation, feature engineering, apply statistical analysis, data visualization, data mining
  • Design and develop algorithms and define path to implementation with IT teams
  • Establish scalable, efficient, automated processes for model development, model validation, model implementation and large scale data analysis
  • Communicate analytical results in a way that is meaningful for business stakeholders and provides actionable insights
  • Provide thought-leadership and oversee execution of diverse projects
  • Have the ability to discover new opportunities where advanced analytical techniques can be leveraged for solving business problems
  • Identify emergent trends and opportunities for future business growth and development
  • 1-3years experience with data science analytics including statistics, machine learning and data mining
  • Masters degree in Mathematics, Statistics, or related degrees
  • Excellent understanding of machine learning and data mining techniques and algorithms
  • Experience with common data science toolkits, such as R, Weka, NumPy. Excellence in at least one of these is highly desirable
  • Proficient with Statistics and Quantitative Analysis
  • Experience with data visualization tools, such as GGplot, D3.js, Tableau, QlikView etc
  • Experience with NoSQL databases, such as Elastic Search, MongoDB, CouchDB, Cassandra, HBase,
  • Great applied statistics skills, such as distributions, statistical testing, regression, etc
  • Proficient in software design and development including Data Structure, OOP/OOD, SQL/NoSQL Database
  • Good scripting and programming skills in Python, Perl, Java, C++, Scala, Go, etc
  • Capability of analytics tools like R, SAS, SPSS preferred
  • Capability of Business Intelligence tools like Tableau, QlikView, etc. preferred
  • Relevant experience in Big Data platforms like Hadoop and its eco-system