Senior Data Scientist

ECS is seeking a Senior Data Scientist to work in our Arlington, VA office.

Job Description:

Responsibilities:

• Coordinate with staff and customers to identify business and technical requirements.
• Produce written documentation and artifacts for all work completed, including the translation of user requirements into technical designs.
• Assist the agency in the development of programming and visualization solutions.
• Troubleshoot and provide support on existing projects or application efforts.
• Engineer data analytic solutions, including prototyping, proof of concept, and full implementation.
• Evaluate, assess, document, and test data security and continuity of operations for systems and programs.
• Ensure compatibility between equipment and software, analyze operational/systems requirements, support design reviews, and present technical briefings.
• Work as RISC liaison to CIO for server/system issues related to AWS and Azure.
• Perform analysis of data for Extraction, Transformation, and Load (ETL) strategies, pattern recognition, and application of analytical tools.
• Review, analyze, and modify existing products including coding, debugging, testing, and documenting.
• Provide guidance to coworkers on business and technical issues affecting projects, such as data access, data quality, storage capacity, and analytic tools and software.
• Assist with training and conference development which may include presentations to large audiences.
• Ensure that quality/security guidelines are followed.

The selected individual will need to live within driving distance of Arlington VA so that they are able to come into the office if needed. Telework will be available, schedule determined by manager.

Required Skills:

• 7+ years’ experience and skill writing coding languages (such as SQL, Python, R, SAS, and Java Scripts).
• 3+ years’ experience working with projects involving machine learning, natural language processing, robotics process automation, artificial intelligence, text and/or data mining, as well as statistical and mathematical methods.
• 1+ year experience working with AWS or Azure services such as Databricks, Data Factory, and Data Lake.
• Capable of supporting all aspects of AI/ML projects along with consulting, development, and implementation activities of ML Ops end-to-end solutions.
• Expert proficiency in common data science tools, including scripted languages (such as SQL, Python, R, and Java Scripts), Integrated Development Environment and analytics platforms, open-source solutions, commercial off-the-shelf tools and hardware-based capabilities to support the data analytic development process and creating models, dashboards, and reports.
• Knowledge and experience using advanced analytic techniques such as machine learning, natural language processing, robotics process automation, artificial intelligence, text and/or data mining, and statistical and mathematical methods.
• Knowledge and experience using business intelligence applications and reporting technologies/methodologies including Data Analytics Expressions (DAX), data Mash-up(M), and Microsoft Power Platform (e.g., Power BI, Power Apps, Power Automate, etc.).
• Knowledge of AWS or Azure Services, including Databricks, Data Factory, and Data Lake.
• Knowledge of SAS Visual Analytics, SAS Enterprise Guide, SAS Studio, Office Analytics, and other SAS tools.
• Knowledge of Extraction, Transformation, and Load (ETL) strategies, pattern recognition, and application of analytical tools.
• Understand the concepts supporting relational databases, data warehousing, data governance, data access, data quality and related areas.
• Knowledge of ODBC connection strings, and other external data source connection protocols.
• Knowledge of scripted languages such as SQL, Python, R, and Java Scripts and the proven ability to create solutions in complex environments, including the use of programming languages to create datasets, visualizations, and interactive reports in various business intelligence applications.
• Skill applying analytical techniques, methods, and processes to business problems demonstrated through a history of accepted modeling and analyses that resulted in meaningful business impact. These include working with unstructured or structured data and converting those data sets using a variety of analyses such as optimization, simulation, classical and spatial statistics, and/or programming languages.
• Skill using advanced analytic techniques such as machine learning, natural language processing, robotics process automation, artificial intelligence, text and/or data mining, and statistical and mathematical methods.
• Strong writing and documentation skills to capture collection of source data, methodology from business rules, and visualization deployment from a myriad of sources and interactions with various stakeholders.
• Strong relational database and querying languages experience.
• Strong verbal and written communication skills.
• Must be able to work effectively in a team environment.
• Understand and follow a software development lifecycle (analysis, design, development, coding, testing, debugging, and documenting).
• Ability to facilitate between business owners and end-users who need to communicate with database administrators and traditional IT support staff.
• Bachelor's Degree in Computer Science, Information Technology, Data Analytics, or related field.

Desired Skills:

• Knowledge of SAS Visual Analytics, SAS Enterprise Guide, SAS Studio, Office Analytics, and other SAS tools.
• Professional Certification(s) in a related field of data science and/or data analytics disciplines preferred

Job Type: Full-time

Pay: $130,000.00 - $150,000.00 per year

Benefits:

• 401(k)
• 401(k) matching
• Dental insurance
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Vision insurance

Schedule:

• 8 hour shift

Experience:

• machine learning, natural language processing: 3 years (Preferred)
• SAS Tools: 4 years (Preferred)
• coding QL, Python, R, SAS, and Java Scripts).: 7 years (Preferred)
• AWS/Azure services: Databricks, Data Factory, and Data Lake.: 2 years (Preferred)
• business intelligence applications/reporting methodologies: 5 years (Preferred)

Work Location: In person