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

CNSS • National Security Systems; Fort Meade (MD); On-site; USD 120,000 - 160,000; Full time

Job summary

The National Security Agency is seeking senior-level data scientists to tackle challenging problems with big data, high-performance computing, and machine learning. You will contribute to complex data problems across foreign intelligence and cybersecurity domains.

Enterprise growth includes opportunities to broaden expertise, participate in internal rounds, and attend technical conferences with experts from industry and academia.

Qualifications

• Degrees in Mathematics or Statistics or Data Science related fields qualify.
• Data Science certificates or 5+ courses in advanced mathematics and/or computer science may be required for certain degrees.
• Entry paths vary by degree level and years of relevant experience, as described (e.g., Associate's with 2 years, Bachelor with 0–2 years, etc.).
• Candidates should have experience in machine learning, data mining, statistics, AI development, or data engineering.

Responsibilities

• 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.
• 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.

Skills

Machine learning

Data analysis

Statistical analysis

Python

Leadership

Data mining

Communication

Education

Bachelor's degree

Master's degree

Doctoral degree

Associate's degree

Tools

SQL

R

Job description

Data science is present in every aspect of NSA's mission to protect the nation. By joining our team, you will tackle challenging problems by leveraging big data, high-performance computing, machine learning and more. We are looking for senior-level data scientists who believe that answers to hard questions lie in the yet-to-be-told story of diverse, complicated data sets. 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. 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.

Note that different degree fields have different requirements as described below.

Degrees in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Data Science, Operations Research, Quantitative/Computational Finance, Econometrics/Quantitative Economics, Computer Science, or Computer Engineering qualify without additional coursework requirements.

Degrees in Engineering, Physical Sciences, Mathematical Biology/Bioinformatics, Life Sciences, Environmental Science, Data Analytics, or Information Science/Systems/Technology, must include either a Data Science certificate from an accredited college/university OR 5 or more courses in advanced mathematics (for example, calculus, differential equations, discrete mathematics, linear algebra, and calculus-based statistics) and/or advanced computer science (for example, algorithms, programming, data structures, data mining, artificial intelligence).

Other degrees must be accompanied by a Data Science certificate from an accredited college/university, and must include 5 or more courses in advanced mathematics AND advanced computer science. At least one course must be from advanced mathematics (for example, calculus, differential equations, discrete mathematics, linear algebra, and calculus-based statistics). At least one course must be from advanced computer science (for example, algorithms, programming, data structures, computer architecture, data mining, artificial intelligence).

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, artificial 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, artificial 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, artificial 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, artificial 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.

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 The ideal candidate has a desire for continual learning along with excellent 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

Knowledge, skills, and relevant experience in programming, formal or informal leadership and one or more of the following are required:

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

Please attach a copy of your resume and all transcripts (unofficial are fine) as part of your application to expedite application processing.