Data Science Engineer Resume Samples

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SJ
S Jast
Sylvester
Jast
39197 Edwina Mountain
Houston
TX
+1 (555) 327 5362
39197 Edwina Mountain
Houston
TX
Phone
p +1 (555) 327 5362
Experience Experience
Chicago, IL
Data Science Engineer
Chicago, IL
Bogisich Inc
Chicago, IL
Data Science Engineer
  • Assist with further processing of the data to aid data scientists during the development process
  • Design, develop, test and deploy a system to generate the Customer Satisfaction Index of our customers based mainly on Network Indicators and other sources
  • Conduct peer reviews of development work completed by team members
  • Write technical specifications and provide documentation of work
  • Define and communicate the work assignments and completion criteria to team members, clarify work expectations, monitor activities and report on status
  • Work with other data scientists and engineers to develop the core predictive analytics and other statistical functionality of our enterprise software platform
  • Develop tooling and infrastructure support data scientists with model development
Los Angeles, CA
Senior Data Science Engineer
Los Angeles, CA
Hartmann, Hirthe and Parisian
Los Angeles, CA
Senior Data Science Engineer
  • Lead cross-functional teams of engineers, technicians, logistics, and service to improve tools for data gathering and analysis
  • Exposure to current tools used by people with disabilities (screen readers and other assistive technologies)
  • Determine and implement mechanisms to improve our data quality
  • Determine root cause to improve throughput by analyzing big data and complex data for patterns
  • Read and conduct research to develop mathematical solutions to our most pressing problems
  • Enthusiasm to work in a fast-paced engineering team
  • Base knowledge of the W3C’s Web Content Accessibility Guidelines v2.0
present
Los Angeles, CA
Principal Data Science Engineer
Los Angeles, CA
VonRueden and Sons
present
Los Angeles, CA
Principal Data Science Engineer
present
  • Work with product manager to help shape data science products and offerings and offer technical inputs
  • Make things work and get things done
  • Like working and being part of an interdisciplinary team
  • Provide thought leadership in technologies and system architecture and drive innovation
  • Design and develop systems for content classification, clustering and content recommendation
  • Lead by example, mentor and provide technical guidance to junior members of the team
  • Develop algorithms that can scale to very large data sets
Education Education
Bachelor’s Degree in Computer Science
Bachelor’s Degree in Computer Science
Northern Illinois University
Bachelor’s Degree in Computer Science
Skills Skills
  • Ability to multi-task, and can quickly switch context and be able to work on multiple projects
  • Ability to quickly create workable solutions to technical problems
  • Attention to detail and robust quality testing, e.g. by creating and running regression suites
  • Strong proficiency in Linux/Unix tools and scripting (Perl, ksh/bash and Autosys)
  • Excellent knowledge of emerging tools & vendors in the market
  • Good knowledge of analysis and optimisation techniques
  • An excellent communicator, open to receiving feedback and able to clearly explain the rationale behind design choices
  • Exceptionally statistical skills, experience of building predictive models using a wide variety of tools and techniques (including: neural network, linear or logistic regression, random forest)
  • Are a great communicator, able to articulate complex concepts in easy to understand language
  • Excellent interpersonal skills and the ability to maintain effective working relationships
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15 Data Science Engineer resume templates

1

Data Science Engineer Resume Examples & Samples

  • Be responsible for building the foundation for the Analytic Center, a scalable platform designed to aggregate, compute and analyze large volumes to data and provide insights to the business and technology stakeholders
  • Be responsible for performing complex data manipulation and analytics, while working with business functions to identify and to respond to complex technical and business problems
  • Be challenged with developing innovative solutions for parallelizing and optimizing analytical algorithms
  • Be part of a team of talented data scientists, analysts, developers and engineers and administrators adhering to the organization's software development standards
  • Use big data fabric technologies to acquire, transform, and provision complex findings using visualization tools
  • Maintain high standard of quality and adhere to best coding practices
  • Strong foundation for compute architecture, parallel processing and data engineering
  • Deep proficiency and a strong track record in Hadoop, Hive, Pig, Python, and other supporting technologies and frameworks
  • 5 yrs. of Object Oriented design & development, web application architecture and development experience
  • Strong proficiency in Linux/Unix tools and scripting (Perl, ksh/bash and Autosys)
  • Experience in building solutions with SQL and NoSQL systems
  • Successful track record building successful data products that leverage large datasets
  • Familiarity with mathematical and statistical model generation using tools such as R, SAS etc
  • Familiarity with machine learning and NLP tools
  • Understanding of the SDLC, good practices and experience with different development and change management tools
  • Experience working with any RDBMS and integration with application
  • Bachelors or advanced degree in an analytical or scientific field such as mathematics, statistics, computer science etc
  • Prior experience working in finance industry is preferred
2

Data Science Engineer Resume Examples & Samples

  • Maintain high standard of quality and adhere to best coding practices.*LI-AK1
  • Good understanding of Retail Banking or Wealth Management business
  • Proficiency with Hadoop, Hive, Pig, Python, and other supporting technologies and frameworks
  • 5+ yrs. of Object Oriented design & development, web application architecture and development experience
  • Good practical knowledge in Linux/Unix tools and scripting (Perl, ksh/bash and Autosys)
  • Deep proficiency with mathematical and statistical model generation using tools such as R, SAS etc
  • Prior experience working in finance industry is preferred*LI-AK1
3

Data Science Engineer Resume Examples & Samples

  • Be part of a dynamic, highly-focused team that is responsible for providing machine-learning insights and SW products that engage TicketMaster's 170+MM users
  • Developing SW to prototype new algorithms for user segmentation, user interest discovery, performance optimization and user response prediction as part of a massively parallel and distributed near-real time collaborative filtering system/marketing platform
  • Productize your algorithms and ideas into full-fledged commercial-grade SW tools that will directly interact with, and affect the experience of million of users, both domestically and internationally
  • 2+ years of industry experience, or equivalent and pertinent course work
  • Proficient in SQL and RDBMS's
  • Experience with/knowledge of frameworks like Hadoop, Pig is desirable
4

Senior Data Science Engineer Resume Examples & Samples

  • Discover new predictive insights in our dataset
  • Design systems that regularly compute new predictive models
  • Read and conduct research to develop mathematical solutions to our most pressing problems
  • Engineer to put your research into practice
  • Ownership of a system that is the core of our intelligence products
  • BS or MS in Computer Science, Computer Engineering, Mathematics. Strength in both fields is necessary; double majors are a big plus
  • 5+ years experience with C, C++, or Java
  • Proven ability at architecting scalable, high performance systems
  • Enthusiasm to work in a fast-paced engineering team
5

Multimedia Data Science Engineer Resume Examples & Samples

  • Design and develop signal processing software capabilities in implementing and adapting innovative multimedia signal processing techniques
  • Design and develop software for data extraction, processing, and analysis in signal processing and algorithm design
  • Communicate project status and technical findings to various levels of leadership
  • Bachelor’s Degree in Engineering, or Physics, or Mathematics, or other related technical degree
  • 3 years of experience in algorithm development
  • Proficiency in programming languages such as MATLAB, R, C/C++, Java or Python for
  • Experience in data extraction and processing techniques
  • Active Top Secret/SCI with Polygraph clearance
  • 6 years of experience in algorithm development
  • An active TS/SCI with poly clearance required
  • Experience in implementing and adapting innovative multimedia signal processing techniques
  • Experience in creating automated tools for metadata extraction and processing
  • Development and reporting of analytic results in the form of technical papers and products
6

Data Science Engineer Resume Examples & Samples

  • Program and develop applications using C++, SQL, Java, Python
  • Work with various volumes of data from multiple disparate sources and perform data analysis and mining to generate solutions to business problems
  • Translate business problems into one or more data science projects/solutions
  • Lead efforts to identify signals in data that can reveal insights for business and process
  • Understand and create business processes to maintain data integrity
  • Collaborate with data architects to ensure that data needed is available
  • Identify new data sources in the network that will create new insights to business needs
  • Explore relevant data through visualization and statistical methods
  • Collect, organize, and prepare data for analysis
  • Tableau and/or Highcharts software experience
  • Semiconductor manufacturing experience
  • Expertise in data mining and analytic methods
  • Experience using statistics to judge data validity and significance
  • Excellent organizational, communication, and interpersonal skills
  • Able to work independently as well as in a group environment
7

Data Science Engineer Resume Examples & Samples

  • Actively participate in complex design and development assignments across the department
  • Thoroughly understand assigned applications and system architecture
  • Conduct research for understanding of new industry technologies as needed
  • Lead and manage multiple project tasks at a time
  • Consistently deliver according to commitments and product plan dates
  • Coordinate team work activities and mentor team members to produce defined deliverables
  • Define and communicate the work assignments and completion criteria to team members, clarify work expectations, monitor activities and report on status
  • Delegate tasks for effective delivery of solutions
  • Collaborate with others on product specification and parameters
  • Write technical specifications and provide documentation of work
  • Accurately estimate assigned project tasks
  • Develop software to HCA standards
  • Conduct peer reviews of development work completed by team members
  • Write unit and functional testing of own code thoroughly, and instrument code thoroughly
  • Build strong relationships within the department and company, including business owners
  • Understand assigned applications and system architecture
  • Lead troubleshooting activities to resolution
  • Work on assignments involving the use of various technologies
  • Develop software with a focus on operations and continuous deployment
  • Mentor other engineers on the applications and system architecture
  • Complete assignments on time and aid others in doing the same
  • Ability to work independently, as well as part of a team
  • Direct the performance of simple, moderate and complex programming assignments within the department
  • Provide after-hours/on-call support as needed
  • Quick learner who easily adapts to functional programming principles and embraces DevOps practices
  • Demonstrated problem resolution oversight for production systems as needed across the department
  • Strategic design, construction and implementation of software in a DevOps environment. This includes selecting, gathering specifications for, designing and implementing solutions for consumers throughout the enterprise
  • Demonstrated extensive experience in large-scale reporting development projects
  • Demonstrated capability to lead team members in technically complex projects in design, development, implementation, and support of solutions
  • Knowledge of clinical data within a healthcare system
  • Ability to communicate and facilitate topics clearly and effectively across department lines; working inside peer groups and receiving guidance from supervisor
  • Demonstrated oral, written and technical communication skills required
  • Self-starter/self-motivated; driven to exceed established goals
  • Works independently, receiving minimal guidance. Acts as a team lead for multi-disciplinary team projects
  • Acts as a mentor and provides direction to colleagues with less experience
  • Technical aptitude to learn and adapt to new industry applications and tools
  • Typical work week hours can vary depending on workload and project deliverables
  • Specific expertise and experience preferred in the following areas: Clojure, Haskell, OCaml, ECMAScript, Ruby, Python, ANSI SQL, Hadoop ecosystem products
  • 7-10 years of relevant work experience required. #LI-TF1 #CB
8

Data Science Engineer Resume Examples & Samples

  • Mastery of one of C++, Python, Java, Scala or equivalent language
  • Experience with Relational databases and NoSQL databases
  • Hands on experience with Hadoop, Spark, Hive/Pig, HBase
  • Solid understanding of the full software development lifecycle
  • Strong ability to evaluate and apply new technologies in a short time
  • Experience in building data science or data analysis tools a plus
  • Machine learning background a plus
  • Familiar with Agile software development process, Test-Driven development and Continuous Integration a plus
9

Data Science Engineer Resume Examples & Samples

  • Minimum 3 years of experience in data science, data warehousing and business intelligence
  • Proven skills working with Relational Databases and BI reporting technologies
  • Proven skills architecting, building and launching new data models that provide intuitive analytics to your customers
  • Proven skills creating and training machine learning algorithms
  • Fluent in SQL, R and Python
  • Experience with Amazon Web Services or other Cloud technologies
  • Detailed understanding of statistics and inference
  • Understanding of database performance tuning techniques
  • Experience with Snowflake, Hadoop and/or other big-data technology stacks
10

Data Science Engineer Resume Examples & Samples

  • Design, develop, test and deploy a system to generate the Customer Satisfaction Index of our customers based mainly on Network Indicators and other sources
  • Help developing new models and indicators of satisfaction
  • Write clean, robust, scalable and efficient code, including development and maintenance of automated tests
  • Work together with the scientific part of the team to build models and indicators
  • Implement models and indicators of network use and customer satisfaction
  • Work closely with our devOps team to analyze the data and leverage already extraction processes
  • Drive and support the collection of new data and the refinement of existing data sources when needed
  • Excellent programming skills in Python (3+ years of experience)
  • Background with BigData platforms (1+ years)
  • Background with Machine learning and data processing (1+ years)
  • Excellent knowledge of Linux environments and shell scripting
  • Excellent understanding of software development paradigms, distributed systems, data structures and algorithms
  • Experience in Continuous Delivery and DevOps
  • Experience in developing large scale distributed systems and high availability/performance/scalable architectures, specifically in Data processing platforms
  • Strong problem solving capabilities
  • Perseverance and creativity to look for alternative options when facing difficulties or negative results
  • Experience with data analysis tools and machine learning libraries (numpy, pandas, R, scikit-learn, etc.)
  • Good understanding of Big Data processing technologies and architectures (hadoop, hive and spark)
  • Test-driven development
  • Git/github
  • Ability to learn new frameworks, APIs and determine the best toolkit for each requirement
  • Experience with agile development working in a rapid application development environment
  • Share knowledge and document it with the rest of the team
  • Passion for applying data science to real-world problems
  • BS in computer science, engineering or related fields
11

Summer Intern, Data Science Engineer Resume Examples & Samples

  • Work closely with engineering, finance, and operations teams to proactively provide insights that directly impact critical business decisions
  • Suggest improvements to data science tools and techniques to help scale the team
  • Academic research experience a plus
  • Strong Programmer - Python, R, Java, and/or C++. Experience with relational database is a plus
  • Experience with big data technologies (Hadoop, Spark, etc.)
  • A passion for problem-solving, comfort with ambiguity, and creativity
  • Demonstrated success presenting complex research data (qualitative and quantitative) in a clear and compelling manner that inspires action
  • Ability to thrive in a dynamic and fast-paced environment and drive change, and collaborate effectively with a variety of individuals and organizations
12

Data Science Engineer Resume Examples & Samples

  • Ensure efficient, high-quality implementation of our machine learning pipeline
  • Implement data integrations & services for machine learning purposes
  • Knowing, understanding and using technical frameworks such as
  • GPU computing frameworks, e.g., TensorFlow
  • Distributed computing engines, Spark/Samza/Flink
  • Distributed data storages such as HDFS/S3, Cassandra, Alluxio whatnot
13

Senior Cyber Security Data Science Engineer Resume Examples & Samples

  • Engineering or Computer Science Degree
  • Big Data technologies
  • Info Security / Cybersecurity Experience
  • BS in computer science, mathematics, engineering or similar
  • Working efficiently with large data sets (Hadoop, Pig, Hive, Impala, Spark or equivalent)
  • Machine learning / statistical modeling
  • Scripting (e.g. Python)
  • Occasional Travel up to 10%
14

Senior Data Science Engineer Resume Examples & Samples

  • Agile Practices
  • Porting/Software Configuration | must have 2+ years experience using *NIX
  • Programming Languages and Frameworks
  • Analytical Thinking
  • Business Product Knowledge
15

Data Science Engineer Resume Examples & Samples

  • 6+ years of experience with increasingly complex algorithm development and programming
  • 3 years of experience with programming and algorithm development, including Java, C++, or Python
  • Knowledge of Artificial Intelligence approaches
  • TS/SCI clearance or TS/SCI clearance with a polygraph
16

Data Science Engineer Resume Examples & Samples

  • Scale efforts to democratise data internally and externally, be an ambassador for data driven culture
  • Become and stay an expert in current and emerging technologies, techniques, and tools
  • Understanding of key machine learning and data mining approaches
  • Ability to multi-task, and can quickly switch context and be able to work on multiple projects
  • Love to learn new things and can do so quickly
  • Like working and being part of interdisciplinary teams
17

Principal Data Science Engineer Resume Examples & Samples

  • Design and build data processing, data mining and machine learning systems that run at scale
  • Build fast changing web apps, big data infrastructures, and real time APIs managing a high traffic
  • Provide thought leadership in technologies and system architecture and drive innovation
  • Lead by example, mentor and provide technical guidance to junior members of the team
  • Contribute to Open Source solutions and communities we use wherever you can
  • Work with product manager to help shape data science products and offerings and offer technical inputs
  • Understand the fundamentals of computer science including programming principles, design patterns, databases fundamentals, and distributed systems
  • Obsess with clean and elegant solutions but do not over engineer
  • Like working and being part of an interdisciplinary team
  • Familiar with many programming languages preferably Scala, Java or Python
  • Expert in "big data" technologies such as Hadoop, Spark, Cassandra, etc
18

Data Science Engineer, Senior Resume Examples & Samples

  • 8+ years of experience as an applications developer, including working with Java, JavaScript, Python, PHP, and C
  • Experience with ASP, C#, and .NET framework
  • Experience with conducting research or analysis using computational models
  • Experience with advanced data analytic techniques and data visualization techniques
  • Ability to configure, design, develop, test, and optimize data applications
  • Experience with Javascript, JQuery, HTML5, and CSS
  • Experience with working in an Agile environment
19

Data Science Engineer Resume Examples & Samples

  • Building data science models for the Fusion team to help protect the bank
  • Responsible for data wrangling in a big data environment
  • Responsible for data preparation & feature creation for machine learning tasks
  • Responsible for gathering data from multiple sources, dealing with incomplete data, and difficult to match records
  • Building REST interfaces which will allow front end developers to access back end data-science work
  • Assessing data to determine if it is fit to carry out a task, and suggesting ways of working around issues that we might face
  • Willing to work to find solutions and articulate / present their ideas
  • Responsible for scaling up algorithms on big data environment
20

Data Science Engineer Resume Examples & Samples

  • Software systems: Linux/Unix, Windows, and MacOS
  • Database management systems
  • Programming Languages: Python, R, SAS, Java, SQL, Shell script, along with proven ability to learn additional languages
  • Databases SQL and noSQL
  • Installation and operation of new software tools
21

Machine Learning & Data Science Engineer Resume Examples & Samples

  • Lead architectural design and development of the chatbot platform ensuring high performance, solid reliability, string resilience, low latency and high flexibility
  • Work closely with product management/leadership teams to design and build new features and insightful metrics focused on making top class user experience
  • Build tools and drive system improvements to make it easier for customer and app teams to adopt and use the platform
  • Provide technical leadership to team members, app developers and stakeholders
  • Bachelor’s degree in a field such as Computer Science, Computer Engineering, Statistics, Economics, Mathematics, Physics
  • Experience in at least one major AI/NLP platform (API.ai, Wit.ai, IBM Watson, Google NLP, etc)
  • Experience of functional programming with Python, Scala
  • Experience with SQL, Spark, Hadoop
  • Experience with Machine Learning and Artificial Intelligence techniques and tools such as Neural Networks, Logistic Regression, Deep Learning, classification and clustering
  • Good concepts and working knowledge of tools in Natural Language Processing (NLP), machine learning, data mining, parallel and distributed computing etc
  • Good grasp of industry best practices in enterprise-class software development
22

Data Science Engineer / Architect Resume Examples & Samples

  • Capable of quickly becoming familiar with new approaches to AI and computational comprehension
  • A good communicator both orally and in writing
  • Excited about working on a team of highly diverse, creative people, all aiming for the same goal and mutually supportive of each other
  • Have what it takes to break new ground and implement radical innovation, facing skepticism, incumbent conservatism, and strong resistance to change in general - with a positive, constructive approach and attitude
  • You have experience in machine learning algorithm development
  • You are deeply curious and knowledgeable about the nuts and bolts of search engines, databases, and other data systems
  • You have some experience working with Hadoop, Spark, etc
  • You have been exploring or working on some of the latest advancements in the deep learning space with Tensorflow, Spark MLLib, word2vec or other Machine Learning platforms
23

Data Science Engineer Resume Examples & Samples

  • Design, extract, normalize, analyze, review and automate analysis utilizing our Data Warehouse, extracts and data exploration tools; coordinate with appropriate subject matter experts on data source requirements
  • Design & develop visual dashboards
  • Identify and use appropriate investigative and analytical technologies to interpret and verify results
  • Review large software implementations to identify transaction flow gaps, design flaws and data integrity issues
  • Actively participates in the completion of department initiatives to support the development of a best-in-class Data Science function
  • Maintain databases and related programs in a thorough and efficient manner
  • 3 years of relevant work experience in Analytics, technology or healthcare required
  • Proficient in the use of Teradata SQL, SAS, Data Visualization (e.g., Tableau, Cognos, Webfocus or other), MS Access, MS Excel, Visual Basic, and or .NET
  • Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts
  • Working knowledge of ‘Big Data’ concepts and Hadoop/Hive, No SQL dbs, Python and/or R tools preferred
  • Working knowledge of statistical analysis, data mining and predictive modeling tools and techniques a plus
  • Strong ability to independently and proactively initiate projects, hypothesize data & business transaction flows and offer technical solutions
  • Strong business analytical skills a must; ability to apply business logic to design and implement data profiling & exploring techniques on large data sets
  • An understanding of risk management methodology and factors
  • Consolidates issues for management level review; develops clear written recommendations, which require minimal editing; presents recommendations and resolves issues with management
  • Demonstrated ability to work independently and within a team in a fast changing environment with changing priorities and changing time constraints
  • Passion for growth and learning new techniques with vigor and enthusiasm. Strong individual contributor with top notch team collaboration skills
  • Take part in training courses to increase skill set and technical capabilities in order to better serve the needs of the Research and Development team
24

Senior Data / Data Science Engineer Resume Examples & Samples

  • Candidate must possess at least a Bachelor's Degree, in Computer Science/Information Technology/Applied Mathematics, Statistic or equivalent with CGPA 3.0 and above
  • 5+ years of experience with relational (SQL) as well as non-relational (NoSQL) database modelling and schema design, dimensional data modelling
  • 5+ years of experience in ingesting data, writing ETLs, Data Pipelines and designing workflows
  • Experience working in Agile Development environment
  • Ability to write complex Analytical Queries and performance tuning
  • Experience with Hadoop technology stack e.g Sqoop, HBase, Hive, Pig, Spark, Oozie, Map Reduce is preferred
  • Knowledge of data mining, data analysis and tools like R
  • Experience in Data Warehousing
25

Principal Data Science Engineer Resume Examples & Samples

  • Help define, design, and build projects that leverage our data
  • Design and develop systems for content classification, clustering and content recommendation
  • Determine and implement mechanisms to improve our data quality
  • Experience building real world machine learning applications in AdTech / marketing or related fields
  • Experience analyzing and working with large datasets
  • Expert-level Java skills and design experience, including significant knowledge of core libraries and common design patterns
  • Experience with open source data processing frameworks is a plus
26

Data Science Engineer, SAP Ariba Resume Examples & Samples

  • Bachelors’ degree in data science or computer science or equivalent experience from a credentialed University or College
  • Strong data processing capabilities – enjoys and feels comfortable analyzing high volume complex customer information
  • Develop and Implement predictive data science models that generate high-value data elements (e.g., performance predictions, behavior classifiers)
  • Develop the analytical infrastructure to support development, testing, release, and maintenance of all the data science, benchmarking, and modeling deliverables defined by Product Management
  • Develop information extraction and text classification algorithms
  • Design and manage multiple databases used by product team
  • Performs database restores and rollbacks
  • Orchestrate data management processes with sales engineers and customers
  • Ability to program in Python (required) and experience with TensorFlow (desirable)
  • Expertise in B2B data cloud products
  • Expertise with Linux and Windows operating systems
  • Experienced in Python based software development for enterprise applications is an asset. Working knowledge of Java is a plus
  • Expertise in working with product development organizations utilizing agile development techniques
27

Data Science Engineer Resume Examples & Samples

  • Work with other data scientists and engineers to develop the core predictive analytics and other statistical functionality of our enterprise software platform
  • Build machine learning models for analysis of unstructured text, extracting themes, sentiment, emotions, key terms, causal relationships, etc
  • Build tools using advanced statistical techniques that automatically analyze employee and survey data, extracting the information that predicts employee engagement, attrition, performance, etc
  • Design and architect software; write production code
  • Experiment and prototype new ideas
  • Meet with clients to stay in touch with the needs of the user
  • Work with product and design teams to plan how to communicate data insights to non-experts
28

Data Science Engineer, Data Science Engineer Resume Examples & Samples

  • Design and develop end-to-end cloud based machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation) with high availability for a wide variety of health related projects with opportunity to improve health quality of millions
  • Building automated & enhanced Data Science stack management with model update/testing (regression, shadow, parallel, A/B) capabilities
  • Build frameworks for experience capture and feed into training data
  • Develop the core Data Science services with near real-time capabilities: Fetch, Search, Predictor
  • Design, build, and deploy platforms, services, abstractions, and frameworks that allow the Data Scientists to conceive of, develop, and deploy their ideas with autonomy
  • Build and maintain tools which allow Data Scientists to perform their own ETL tasks
  • Execute continuous integration, continuous deployment, and DevOps best practices
  • Work with large volumes of both structured and unstructured data
  • Produce documentation for code, APIs, and procedures
  • Collect, measure, and interpret process performance data; using tools such as Pareto charts, flow charts, process maps, Cause and Effect diagrams, scatter plots, histograms, and control charts
  • Troubleshoot and triage problem reports, resolve, and escalate as required
  • Ensure the appropriate identification of root causes through effective use of data analysis tools and techniques
  • Perform responsibilities above with an increased degree of independence and self-direction
  • Provide higher level consultation on data findings and recommendations
  • Works and interacts across the organization with a variety of business units
  • Develop distributed learning algorithms for classification and regression
  • Establish critical foundational information extraction and retrieval capabilities
  • Perform responsibilities above with an increased degree of independence and self-direction. Take initiative to pursue larger-scope projects
  • Design, and implement online experiments frameworks, including A/A and A/B testing, in a variety of configuration environments
  • Devise creative solutions for building highly scalable distributed production systems for both internal and external customers
  • Provide architectural input and review of services and APIs for data ingest and dispersal within the ecosystem
  • Provides higher level analysis and data interpretation in support of strategy development, program implementation and analysis
  • Create influential metrics, dashboards, and presentations that use information to influence senior leadership on business trends and strategies
  • Acts as a data and analytics subject matter expert on cross-functional teams brought together to work toward the development and execution of strategic initiatives
  • Responsible for developing new data solutions for the enterprise, building statistical models
29

Data Science Engineer Resume Examples & Samples

  • Work very closely with data scientists to find and solve engineering pain-points by building scalable, general-use platforms
  • Develop tooling and infrastructure support data scientists with model development
  • Help champion a data-driven culture and push long-term business value creation through development of best-in-class data science tools
  • MS or PhD in Computer Science or Engineering (or related field)
  • A good understanding of machine learning and statistical analysis
  • Highly skilled with Python, Java, and SQL
  • Proven track record of developing, maintaining, and deploying data services
  • Strong ability to work autonomously and take ownership of a project
30

Data Science Engineer Resume Examples & Samples

  • Ability and appetite to pick up new technology and languages quickly
  • Ability to quickly create workable solutions to technical problems
  • Experience in programming languages, e.g. could include some or all of C, Java, Python, Linux scripting, SQL, Docker
  • Attention to detail and robust quality testing, e.g. by creating and running regression suites
  • Knowledge of machine learning techniques such as logistic regression or random forests (desirable)
  • Degree (ideally Masters or PhD) in Computer Science, Artificial Intelligence, Machine Learning, Applied Statistics, Physics, Engineering or related field. Candidates are welcomed direct from completing a PhD, and candidates with relevant experience are also encouraged to apply
31

Senior Data Science Engineer Resume Examples & Samples

  • Design and implement analytics and reporting tools to support key business decisions
  • Determine root cause to improve throughput by analyzing big data and complex data for patterns
  • Develop algorithms and applications to apply mathematics to data; translate data into intelligence to solve a variety of business problems and determine optimal business strategies
  • Collaborate with cross-functional teams to identify optimal solutions using operations research and answering business questions where analytics can be most impactful
  • Drive all aspects of analysis including data acquisition and manipulation, programming, data visualization, documentation, and presentation of results
  • Lead cross-functional teams of engineers, technicians, logistics, and service to improve tools for data gathering and analysis
32

Data Science Engineer Resume Examples & Samples

  • Unit Testing
  • Real-time data processing
  • Familiarity with data historians
  • Data Science / Algorithms - Good exposure to a wide variety of algorithms and analytic approaches; understanding of where different techniques can be applied under different data scenarios
  • C# - Good general skills. Work is primarily in real-time processing, threading, WinForms, and runs in real-time as a series of windows services
  • General – Strong analytic skills, willingness to learn and support multiple areas of the software
  • Strong communication - Must be able to communicate complex topics (like new algorithms) to technical users that are not subject matter experts in data science, such as engineers and technical support members. Must be able to clearly articulate different scenarios for testing and feedback with other team members
33

Senior Data Science Engineer Resume Examples & Samples

  • Experience of Big data and distributed platforms, NoSQL, Big data store, Data warehouse
  • Batch and streaming large-scale data processing (Apache Beam, Apache Spark) and advanced SQL
  • Python general purpose and for data science (Pandas, Scikit-learn,…)
  • Micro services, virtual environments, containers, advanced distributed version control system
  • Previous experience in using advance statistical techniques for developing data solutions
34

Lead Data Science Engineer Resume Examples & Samples

  • Mastery of the data models across Teradata, Hadoop, Unix, and SAS platforms
  • Translate business opportunities into analytic deliverables that drive actionable insights and have direct bottom line impact on topics such as
  • Multi-touch attribution / evaluate the ROI of marketing, with the goal of helping the organization understand the best way to optimize spend against key marketing objectives
  • Build ETL to house externally and internally derived data sources across Teradata, TD Aster, Hadoop, SAS environments
  • Partner with IT, Marketing and Vendor teams to ensure that accurate and comprehensive tracking and delivery solutions are in place
  • Build behavioral-based targeting solutions for outbound marketing deployments, such as CLV or merchandise-driven style affinity
  • Create solutions that optimize site conversion, such as on-site search performance, content to product recommendations, and other site improvements
  • Communicate findings to cross-functional teams (creative, merchants, finance, marketing, etc.) to drive decisions and action
  • Production-quality scripting that delivers personalized marketing experiences to the customer at scale
  • Author application code as well as shell scripting to automate execution in run-time environments
  • Technical mentorship on best-practices in efficient computing, data management, and toolsets
  • Predictive models (Linear, Logistic, Proportional Hazards, Boosted Regression Trees)
  • Clustering (K-means, Fuzzy, C-means, Hierarchical, Mixture modeling)
  • Classification (Decision Trees, Logistic, Deep Learning, SVM, Random Forest)
  • Natural language processing
  • Sentiment analysis
  • Have passion for data and overwhelming curiosity to learn
  • Masters/Advanced degree in Statistics, Mathematics, Operations Research, Computer Science or other quantitative field with 2-5 years of industry experience
  • OR Bachelors degree in above mentioned quantitative field with 3-6 years of industry experience working directly with large and diverse data assets, data analytics and related research
  • Experience in data warehousing including dimensional modeling concepts
  • Develop strategies to extract, resolve, and unify information of various types from numerous disparate data sources (structured and unstructured)
  • Maintain, enhance, and optimize the data pipeline for scalability and reliability
  • SQL skills (self rated scale of minimum 8 out of 10)
  • R, Python (self rated scale of minimum 5 out of 10)
  • Shell scripting (self rated scale of minimum 8 out of 10)
  • Appetite to work across multiple platforms, such as Teradata, Unix, Linux, Hadoop/Hive, SAS
  • Priority consideration will be given to the candidate having experience with Machine Learning techniques for classification, regression, clustering, and topic modeling
  • Familiarity with Adobe Analytics is a plus
  • Retail experience is a plus
  • LI-AB
35

Data Science Engineer Resume Examples & Samples

  • Develop, operate, support and continually optimise a common data analytical platform that can support rapid discovery and deployment of data products and enables a community of any data scientists to easily obtain insight
  • To foster and cultivate a culture of “agile emergent design” so that it will enable the smooth and rapid transitioning of prototype data products into robust product assets
  • To establish credibility and thought leadership in the area of data science and to engage with the enterprise architecture function to ensure best practice, influence and contribute to the development of strategic vision for data usage within the company
  • Develop sophisticated and innovative data products that will have considerable and measurable impact; either in cost reduction, revenue increase or enable new business opportunities
  • Take responsibility for the delivery of specific pieces of Data Science work, managing the overall process of delivery and taking responsibility for data, modelling and communication of analysis to stakeholders; including clear and actionable insight through advanced analysis and interpretation of multiple complex data sets
  • Contribute into the Data Science strategic road-map
  • Contribute and support Data Science best practices, knowledge and standards
  • Evangelise the use of data and methods; challenging existing paradigms in a constructive manner that demonstrate and promote the value of the Data Science capability
  • Identify, own and manage the risks involved in running our business appropriate to my role, in line with the company risk framework
  • Identify, evaluate and recommend emerging and established commercial and open-source technologies that can be used to drive value from existing applications, systems or functions
  • Strong academic background ideally within computer science, physics or maths based or equivalent
  • Advanced SQL for data manipulation or experience of managing Tera-scale data sets within an analytical function
  • Advanced working knowledge of unix-like environments; including shell scripting, version control, services etc
  • Python and/or Java
  • Strong analytical, quantitative, problem-solving, and critical thinking skills
  • Good written, verbal and presentation communication skills
  • Ability to work collaboratively with other business units in order to achieve common objectives
  • Organised self-starter, with drive and commitment; able to finish work with little supervision
  • Excellent interpersonal skills and the ability to maintain effective working relationships
  • Exceptionally statistical skills, experience of building predictive models using a wide variety of tools and techniques (including: neural network, linear or logistic regression, random forest)
  • Experience of commercial data science or analytics software ( e.g. R, SAS, SPSS, MATLAB etc.)
36

Data Science Engineer Resume Examples & Samples

  • Develop, evangelize strategy, roadmap for Technical Data Science in consultation with senior business partners, Data science groups and Technology leadership
  • Research trends and innovation in analytics to guide initial uses and potential adoption
  • Translate strategic analytics requirements into Analytics tools and infrastructure
  • Design, run and evaluate experiments to monitor key sales / customer / store, product and program metrics, understand root causes of changes in performance
  • Design/ Run experiments to answer targeted questions
  • Research, prototype, develop / adapt emerging algorithms, empirical methods and quantitative tools to analyze high volume historical data and high velocity streaming data
  • Operationalize Analytical models at scale
  • Leads innovative packaging and presentation of insights to business and broader analytics community
  • Identify and promote best practices across the organization
  • Coach and mentor a community of Data Science engineers and citizen data scientists
  • Leadership role in large scale Analtytics programs (2+ years)
  • Analytics consulting in Retail industry (2+ years)
  • Statistical Modelling & Machine Learning with proficiency in using packages / languages such as SAS/R/Python (3+ years)
  • Experience with Big Data Systems ( such as Hadoop) (2+ years)
  • Overall experience in Data Engineering & Analytics (7 years)
37

Data Science Engineer Resume Examples & Samples

  • Extract data from internal systems and work closely with the modeling teams to prepare data for analysis
  • Assist with further processing of the data to aid data scientists during the development process
  • Translate business requirements into S analytic implementation code for use within internal systems and models
  • Develop reports and analysis to inform management on model performance, and/or tools to facilitate understanding of model results
  • Model/Analytics Implementation, deploy and maintain model performance monitoring processes. Follow standard SDLC processes and agile Scrum program management principles. Become one of the Data science/Predictive Analytics team experts on internal servers and databases
  • Be a positive team player, comfortable working in a team environment setting for project deliverables and delivering High quality results as well meeting project deadlines
  • Develop and/or maintain a library of commonly used macros/modules and programs for data extraction, transformations, analytic model scoring execution, monitoring and performances etc
  • Support existing Analytics processing in a tier-production environment prioritizing SLA returns for claims processing of Statistical Models
  • 5+ years of development experience with SAS (Unix), SAS EG & SAS Tools
  • 5+ years of experience with SQL, Oracle or DB2 or MS SQL Server or Hadoop
  • 5+ years of software development and engineering experience on SAS Unix/Grid environments
  • Knowledge and process experience using SDLC for Advanced Analytics implementations and support for predictive analytics models
  • Claim Data Analytics Integration with SAS/R/Python or other relevant ETL development experience
  • Microsoft Office Products experience
  • Experience with Hadoop eco system
  • Development experience in Data sourcing from Netezza, Teradata or Hadoop clusters
  • Agile Project Management experiences on Analytic development and deployment
  • XML domain knowledge
  • Knowledge of ICD-10 coding of Medical claims
  • R, Python, Spark, HBASE, HIVE or H20 development experience
  • Agile methodology analytics development experience
38

Data Science Engineer Resume Examples & Samples

  • Enhance our machine learning software with the latest in machine learning algorithms
  • Employ statistical modeling and analysis to generate new features for our models
  • Create systems that monitor dataflow on a real-time basis
  • Perform market analyses to react to changing market conditions
  • Design systems that generate predictive models for a variety of signals and tasks
  • Develop mathematical solutions to our most pressing problems
  • Engineer to put research and solutions into practice
  • BS or MS in Computer Science, Computer Engineering, or Mathematics
  • Knowledgeable in statistics and data analysis
  • Experience translating math into efficient code
39

Data Science Engineer, Infra Resume Examples & Samples

  • Design pipelines that generate predictive models for a variety of signals and tasks
  • Architect systems that crunch data and provide queryable interfaces for stakeholders
  • Ensure signals robustly make it to online prediction tasks in real-time
  • Integrate with external data sources to feed into existing datasets
  • Engineer data formats that help answer analysis questions efficiently
  • BS in Computer Science or Computer Engineering
  • 3+ years experience with C, C++, Java, or other performant language
  • Experience with manipulating large datasets
  • Ability to architect scalable, high performance systems
  • Experience in distributed computing frameworks and paradigms
40

Data Science Engineer Resume Examples & Samples

  • BSc or MSc in computer science, mathematics, statistics or quantitative methods (or equivalent years’ experience)
  • Strong interest in applied modelling, analytics and machine learning
  • Experience of working in a research or innovation environment a plus
  • Design complex, data-rich solutions that support data driven workflows and decisions
  • Work with the team to understand user goals and requirements alongside global stakeholders and customers
  • Implement, operate and own a data analytics environment to focus on innovation initiatives
  • Champion a data science and data driven opinion across innovation innitiatives
  • Build feature extraction models, ETL processes, analytical and statistical models
  • Utilise, implement and research machine learning and predictive analytical methods
  • Provide technical support and be a resource to internal and external modellers
  • Summarise and communicate conclusions and solutions to analytic and non-analytic stakeholders
  • Investigate and develop new innovative statistical techniques
  • Expertise in development languages including but not limited to Python, Scala, Java, R, Julia
  • An excellent communicator, open to receiving feedback and able to clearly explain the rationale behind design choices
  • Good knowledge of analysis and optimisation techniques
  • Good understanding of statistical and machine learning methods applied to data analysis
  • An understanding of various statistical methodologies including linear regression, logistic regression, and other advanced analytic techniques
  • Knowledge of managing, manipulating and transforming data from a variety of sources
  • Experience with large datasets is an advantage
  • User of either R, Python, SPSS, SAS, MySQL or equivalent analytic software
  • Experience with big data and machine learning platforms including but not limited to Apache Spark, Flink, Beam, Theano, Tensorflow or equivalent
  • Excellent knowledge of emerging tools & vendors in the market