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.

• Requires compiling various data sources via computer scripting, statistical analysis, data modeling, etc. This position requires being
  able to develop rapid protypes and analytics to show metrics on sensor performance.
• A SIGINT collection/ targeting background is a strong foundation for this team.
• Knowledge of interacting with APIs; reading/using/building tools to retrieve data from them.
• Python using Jupyter and Pandas proficiency is required.
• Data Visualization exp using Plotly is a plus. XKS, DX, GM proficiency, Networking, SQL, HTML or Pyodide exp are also a plus.
• Team based setting, a strong self starter is a plus.
• Primary focus is having Al/ML experience to impact and assess large datasets. This includes data modeling, computational mathematics, qualitative and quantitative techniques, data visualizations and Al/ML model development and deployment. Advanced statistical and predictive modeling. Large-scale data processing (e.g., Spark, cloud data platforms). Python and SQL proficiency. Data visualization using Tableau, Power BI, or Python libraries. Automated analytics workflow development. Ability to translate complex data into strategic insights.
  
  Target knowledge or experience is a plus. Strong collaboration is preferred.
• 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.