Data Scientist - Experienced to Expert Level (Maryland)

Responsibilities

Data science at the National Security Agency (NSA) involves using mathematics, statistics, computer science, and domain-specific knowledge to analyze and interpret data. It includes roles such as AI Engineering, Data Engineering, ML Ops Engineering, and Human Perception and Cognition Engineering. Key responsibilities may involve:

• Exploring data analysis and model fitting to reveal data features of interest.
• Using machine-learned predictive modeling.
• Constructing usable data sets from multiple sources to meet customer needs.
• Identifying and analyzing anomalous data (including metadata).
• Developing conceptual design and models to address mission requirements.
• Developing qualitative and quantitative methods for characterizing datasets in various states.
• Performing analytic modeling, scripting, and/or programming.
• Working collaboratively and iteratively throughout the data-science lifecycle.
• Designing and developing analytics and techniques for analysis.
• Analyzing data using mathematical and statistical methods.
• Evaluating, documenting, and communicating research processes, analyses, and results to customers, peers, and leadership.
• Creating interpretable visualizations.

Qualifications

The qualifications listed are the minimum acceptable to be considered for the position. Applicants must pass the Data Science Examination (DSE) to be considered. Additionally, transcripts for each academic institution are required prior to being invited to interview with Agency data science professionals.

Experience

• Programming experience.
• Experience in machine learning, data mining, statistical analysis, statistical consulting, artificial intelligence development, computational science, software engineering, technical writing, data visualization, or data engineering.
• Experience in formal or informal leadership roles.

Competencies

• A desire for continual learning.
• Excellent analytical, problem-solving, communication (oral and written), and interpersonal skills.
• Ability to solve complex problems.
• Proficiency with critical thinking and reasoning to make analytic determinations.
• Effectiveness in working in a collaborative team environment.
• Able to bridge the gap with both technical and non-technical audiences.
• Able to provide technical leadership in formal or informal roles.

Knowledge, Skills, and Relevant Experience

• Designing and implementing machine learning.
• Data mining.
• Statistical analysis.
• Statistical consulting.
• Artificial Intelligence development.
• Computational science.
• Software engineering.
• Technical writing.
• Data visualization.
• Data engineering.

Pay, Benefits, & Work Schedule

Salary offers are based on candidates' education level and years of experience relevant to the position. Benefits include a comprehensive package, and the work schedule is Monday - Friday, with basic 8hr/day work requirement between 6:00 a.m. and 6:00 p.m. (flexible).

Application Instructions

Apply soonest, as job postings can close earlier than stated end dates due to changes in requirements. Ensure your resume and transcripts are included in your application. Certify that you are using your own words and did not use a consultant or AI such as ChatGPT or Copilot.