Data Scientist - Experienced to Expert Level (Maryland)

Responsibilities

Data science at the National Security Agency (NSA) involves using elements of mathematics, statistics, computer science, and application-specific knowledge to gather, make, and communicate principled conclusions from data. It encompasses AI Engineering, Data Engineering, ML Ops Engineering, and Human Perception and Cognition Engineering in addition to traditional data science applications.

• Exploring data analysis and model-fitting to reveal data features of interest
• Using the 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 will be asked to complete the Data Science Examination (DSE) which evaluates their knowledge of statistics, mathematics, and computer science topics that pertain to data science work.
• Passing this examination at a local testing site is a requirement in order to be considered for selection into a data scientist position.
• Transcripts for each academic institution are required prior to being invited to interview with Agency data science professionals and should be submitted as part of the online application.
• Experience must include both programming and one or more of the following: designing/implementing machine learning, data mining, statistical analysis, statistical consulting, artificial intelligence development, computational science, software engineering, technical writing, data visualization, or data engineering.
• Experience must also include formal or informal leadership.

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

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