Engineer, Data Science Job Description
Engineer, Data Science Duties & Responsibilities
To write an effective engineer, data science job description, begin by listing detailed duties, responsibilities and expectations. We have included engineer, data science job description templates that you can modify and use.
Sample responsibilities for this position include:
Engineer, Data Science Qualifications
Qualifications for a job description may include education, certification, and experience.
Licensing or Certifications for Engineer, Data Science
List any licenses or certifications required by the position: AWS, CFA, CQA, CQE, ASQ, MS, ITIL, MRMC, R&D
Education for Engineer, Data Science
Typically a job would require a certain level of education.
Employers hiring for the engineer, data science job most commonly would prefer for their future employee to have a relevant degree such as Bachelor's and Master's Degree in Computer Science, Engineering, Statistics, Science, Mathematics, Math, Physics, Software Engineering, Technical, Education
Skills for Engineer, Data Science
Desired skills for engineer, data science include:
Desired experience for engineer, data science includes:
Engineer, Data Science Examples
Engineer, Data Science Job Description
- Support continuous improvement by investigating alternative algorithms and technologies and presenting them for architectural review
- GPU computing frameworks, , TensorFlow
- Design, extract, normalize, analyze, review and automate analysis utilizing our Data Warehouse, extracts and data exploration tools
- Work on incredibly hard problems in computer vision & artificial intelligence that are of value in the real world
- Create world-class products and cutting edge concepts
- Work in a highly visible, dynamic team that provides continuous opportunities for learning and growth
- Join a company with a strong commitment to our teams maintaining a healthy work life balance and providing a top tier benefits program
- Analyze petabyte size data to identify useful relations, patterns, and features that are predictive of user behaviors, preferences, intents, interests, brand affiliation, and Continuously identify and explore new and unconventional data sources
- Develop innovative techniques to collect performance data and measure the impact of online advertising
- Build machine learning models for analysis of unstructured text, extracting themes, sentiment, emotions, key terms, causal relationships
- Familiarity with agile methodologies (SCRUM)
- Experience with cloud providers such as Amazon and Rackspace
- Ability to think out of the box, and leverage techniques from diverse areas of computer science, statistics, operations research
- Prior achievements in handling data (including internship/job/data competitions)
- BS/MS degree in Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, Econometrics, or equivalent/related degree
- 3+ years of development experience using Big data technologies including Hadoop, Pig, Hive, HBase, Spark
Engineer, Data Science Job Description
- Developing and integrating basic REST APIs to interact with containerized analytics solutions (swagger / node.JS / flask / bottle)
- Experience configuring cloud platforms and deploying big data tools and solutions with technologies like AWS EMR, RDS, Redshift and DynamoDB
- Lead development of machine learning models/predictive analytics techniques leveraging both repeatable patterns in data and discovering new features that reduce variability, improve quality and enhance product yields in magnetic head wafer manufacturing operations
- Understand challenging business problems and develop tools & techniques to find patterns and insights within structured and unstructured data generated in nanoscale manufacturing environment
- Manage data analytics project requiring critical thinking about the relationships of different metrics measured (metrology) and process steps to land the right features (physics & integration) for a given model
- Prototype creative solutions for improving product performance predictability, and be able to lead others (Domain/IT stakeholders) in crafting and implementing smart factory solutions in wafer operations
- The liaison between production platform and data scientist teams
- Define and implement models and processes to intelligently deliver and self-heal other models and infrastructure systems in production
- Work with platform and data scientist team to help define the development to production work flow
- Produce production ready models provided by the data scientist team
- Expert knowledge of Hadoop, particularly Hive and Pig
- Familiarity in building a layered architecture database with multi stage tables for several kinds of business analytics
- Ability to prioritize and execute multiple tasks in a highly dynamic environment with a results oriented mindset
- Data modeling experience and familiarity with all sorts of standard data models
- Knowledge of working with business intelligence tools (e.g., Tableau, MicroStrategy)
- Strong problem solving with acute attention to detail and ability to meet tight deadlines and project plans
Engineer, Data Science Job Description
- Communicate findings to cross-functional teams (creative, merchants, finance, marketing, ) to drive decisions and action
- Author application code shell scripting to automate execution in run-time environments
- Propose, implement , A/B test and deploying new techniques in video recommendations
- Identify and propose new solutions to build data insights
- Identifying and building the necessary infrastructure
- Work closely with Product teams in architecting, designing, and implementing features that scale
- Develop sample integrations, tutorials and documents for working with Jupyter Notebooks and the ArcGIS System
- Perform bug fixes and maintenance tasks for relevant and related products
- Write samples and guides using Jupyter Notebooks, SDK guides and blog posts
- Design, test, release, and support ArcGIS software for geoprocessing and analysis to enhance overall product quality and applicability for supporting data science workflows and needs
- Hardware support for servers, desktops, laptops tablets and Apple/Android products
- Ability to translate technical problems to a business user
- Understanding of data science
- 5+ years of experience creating predictive models to help businesses identify and understand drivers of product quality and issues
- Experience using open source statistical computing toolkits like R, Apache Mahout, and scikit-learn
- Familiarity with Apache Spark and ElasticSearch
Engineer, Data Science Job Description
- Ability to separate useful information from data noise and analyze that useful information to extract new insights
- Interpret patterns and trends in complex datasets using advanced analytical tools and models
- Participates in cross-functional groups to acquire deep understanding of transportation challenges and translate that into executable outcomes using data and statistical methods
- Interacts with internal and external customers using data visualization tools to communicate and interpret results
- Ensures solutions will meet financial goals and provide cost savings
- Assist in the development of the Freight Network Team
- Comfortable working in an ambiguous environment, resolve situations quickly, communicate status of problem, and work with the appropriate subject matter experts to resolve
- Designs and implements innovative, pioneering data-driven insights to solve complex business problems
- Works within Data Labs to proto-type solutions during Research and Development phases
- Participate in the process turn-over from development to production, , submitting requests to our IT colleagues and/or productionalizing through the Data Sciences Data Management team
- Ability to lead successful integration activities that deliver desired results by effectively planning, identifying resources, and managing schedule, resources, and scope
- Comfortable with an Agile development process
- Possess the ability to work in several areas of a development life cycle as part of a team or independently
- Basic understanding of Master Data Management principles and practices
- Experience in collaborating with global team members to drive results
- Ability to define and ensure process adoption and compliance
Engineer, Data Science Job Description
- Deployments of Machine Learning services written in Python and running in Docker containers on premise or in the cloud.Collaborate with the Data Scientists on the team to bring models into the real world
- Selecting features, building and optimizing classifiers using machine learning techniques based on input from domain experts across the company to identify anomalous behavior
- Taking a strong role in growing data science capabilities within the threat intelligence and security organizations
- Swiftly create prototypes and functional prototypes
- Work as part of a fast-paced team, being equally comfortable either contributing to a larger effort delivering a result on their own
- Think outside the box, innovate to requirements
- Contributing member of a high performing, agile team focused on next generation data & analytic technologies • Automation of environment and platform configuration and deployment with tools such as Chef and Ansible
- Use data science techniques and tools to explore and create solutions
- Identify, extract, clean, and transform data
- Work with business units and others to understand the problem space and challenges
- Experience with MPP data platforms (Hadoop, Teradata) a plus
- Experience with NoSQL databases (HBase, Cassandra) a plus
- Advanced linux shell expertise and a very high comfort level with crons, config files, user administration, Must be able to analyze loads and tune job scheduling
- First class degree from a top university, in a technical subject Engineering, Mathematics, Physics, Computer Science
- Experience with Oracle, Redshift, Teradata
- Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark)