Data Scientist

Requires Top Secret/SCI with Full Scope Poly

• Devise strategies for extracting meaning and value from large datasets.
• Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
• Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
• Effectively communicate complex technical information to non-technical audiences.
• Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly-shifting collection, processing, storage and analytic capabilities and limitations.

• Experience with process automation for reporting. Includes designing scalable extract transform load (ETL) workflows, implementing incremental and batch data ingestion with robust data validation.
• Candidate will complete data transformation & modeling using SQL and Python (Pandas, PySpark, or Polars is preferred). Requires preprocessing, minimizing, filtering, normalizing, aggregating, and reshaping datasets for reporting. Automating dashboards using Power BI, Tableau etc. is a plus. Candidate will maintain python automation packages.
• A Bachelor’s degree and 10 years of relevant experience. An Associate’s degree plus 12 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.
• Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g.
  
  C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support a single or multiple domain areas, and/or software engineering.
  
  Experience in more than three areas is strongly preferred.