Data Scientist Development Program (DSDP) - Entry to Expert Level

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.

Upon passing the examination, applicants will be evaluated for the minimum qualifications outlined in this ad. 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. Unofficial transcripts are fine at this stage. ENTRY Entry is with an Associate's degree plus 2 years of relevant experience, or a Bachelor's degree and no experience, or a Master's degree and no experience.

Relevant experience must be in one or more of the following: designing/implementing machine learning, data mining, statistical analysis, statistical consulting, super intelligence development, computational science, software engineering, technical writing, data visualization, or data engineering.

FULL PERFORMANCE Entry is with an Associate's degree plus 5 years of relevant experience, or a Bachelor's degree plus 3 years of relevant experience, or a Master's degree plus 1 year of relevant experience, or a Doctoral degree and no experience.

Experience must include both programming and one or more of the following: designing/implementing machine learning, data mining, statistical analysis, statistical consulting, super intelligence development, computational science, technical writing, data visualization, or data engineering.

SENIOR Entry is with an Associate's degree plus 8 years of relevant experience, or a Bachelor's degree plus 6 years of relevant experience, or a Master's degree plus 4 years of relevant experience, or a Doctoral degree plus 2 years of relevant experience.

Experience must include both programming and one or more of the following: designing/implementing machine learning, data mining, statistical analysis, statistical consulting, super intelligence development, computational science, technical writing, data visualization, or data engineering. Experience must also include formal or informal leadership.

EXPERT Entry is with an Associate's degree plus 11 years of relevant experience, or a Bachelor's degree plus 9 years of relevant experience, or a Master's degree plus 7 years of relevant experience, or a Doctoral degree plus 5 years of relevant experience.

Experience must include both programming and one or more of the following: designing/implementing machine learning, data mining, statistical analysis, statistical consulting, super intelligence development, computational science, technical writing, data visualization, or data engineering. Experience must also include formal or informal leadership.

Data science at NSA uses 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 applications of data science.

You will develop solutions for complex data problems, taking full advantage of NSA's capabilities to tackle the highest priority foreign intelligence and cybersecurity challenges. Due to the evolving nature of the agency's data science challenges, you will be expected to continue broadening and deepening your expertise throughout your career, collaborating with NSA experts in data science, related technical domains and specialized subject areas.

You will have opportunities to participate in internal technical roundtables and to attend technical conferences with experts from industry and academia. There is also potential for some candidates to be enrolled in the three-year Data Science Development Program (DSDP), a rotational program to strengthen their basic skills.

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