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 AI Engineering, Data Engineering, ML Ops Engineering, and Human Perception and Cognition Engineering, among others. Key responsibilities may include:

• 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.

Pay, Benefits, & Work Schedule

Pay: Salary offers are based on candidates' education level and years of experience relevant to the position. Salary Range: $132,751 - $197,200 (Senior, Expert).

Benefits: NSA offers a comprehensive benefits package.

Work Schedule: This is a full-time position, Monday - Friday, with basic 8hr/day work requirement between 6:00 a.m. and 6:00 p.m. (flexible).

Competencies

The ideal candidate has a desire for continual learning along with excellent analytical, problem-solving, communication (oral and written), and interpersonal skills who is:

• Accountable
• Proactive
• Detail oriented
• Able to solve complex problems
• Proficient with critical thinking and reasoning to make analytic determinations
• Effective at 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

Required knowledge, skills, and experience in programming, formal or informal leadership, and one or more of the following:

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