Data Scientist

Responsibilities

• Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big-data environment.
• Demonstrate expert knowledge of Python, and Jupyter Notebooks and/or Jupyter Labs.
• Author cogent and logical scripts using Python and other applicable languages in a virtual environment using common Integrated Development Environments (IDE) such as VS Code, Spyder, PyScript, or Jupyter Notebooks.
• Develop and use advanced software programs, algorithms, query techniques, models to solve complex intelligence problems, and automated processes to normalize, integrate, and evaluate data.
• Debug existing and future Python code; refactor legacy code to ensure continued security, functionality, and compatibility.
• Document and block-comment all code to ensure recoverability and error-checking, and enhance reading, checking, and maintaining code in accordance with common data science and coding standards, such as PEP-8 for Python,5 or using style-guide features embedded in common IDE applications, such as Spyder, VS Code, PyScript or others upon approval by the Government.
• Collaborate across multi-discipline teams to ensure connectivity between various data sources and business problems.
• Identify meaningful insights, interpret, and communicate findings, plus make recommendations to stakeholders.
• Analyze requirements and evaluate technologies for data science capabilities including Natural Language Processing, Machine Learning, predictive modeling, statistical analysis, and hypothesis testing.
• Maintain awareness of emerging analytics and big-data technologies.
• Complete required course NSA NETA1400 (Technology Fundamentals for Analysis); recommended completion of any of the following NSA Courses: NETA2402/NETA2108 (Analysis II), RPTG2238, RPTG2235, RPTG3225, RPTG3222 (Basic Analytical Reporting) or equivalent curriculum.
• Complete recommended certifications: Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE), Associate Big Data Analyst (ABDA), and Senior Data Scientist (SDS); Google Data Analytics Professional Certificate; IBM Data Science Professional Certification.

Qualifications

• Minimum Experience: Citizenship: Must be a US citizen
  Clearance: Must have and be able to maintain a Top Secret (TS) with Sensitive Compartmented Information (SCI) adjudication
  Education: Bachelors Degree
  Years of Experience: 7+ years experience in data science/analytics engineering/software development in big-data environments.
• Additional Experience: Expert Python skills; heavy use of Jupyter Notebooks/Labs and common IDEs (e.g., VS Code/Spyder).
• Proven ability to build and sustain automated data workflows (ingest/normalize/integrate/enrich/evaluate) using algorithms, queries, and models.
• Strong SDLC skills: debugging, refactoring legacy code, and maintaining secure/compatible codebases.
• Code quality discipline: clear documentation/block comments and adherence to PEP-8 (or equivalent style enforcement).
• Working knowledge of data architecture and ability to collaborate across multi-discipline teams to connect data sources to mission problems.
• Ability to communicate findings and recommendations to stakeholders.
• Experience applying/evaluating ML/NLP, predictive modeling, and statistical methods (hypothesis testing).
• NSA NETA1400 (Technology Fundamentals for Analysis) completion, or Government-approved equivalent.