Data Engineer / Data Scientist - Entry to Expert Level (Maryland, Hawaii & Color

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Data Engineer / Data Scientist - Entry to Expert Level (Maryland, Hawaii & Colorado Locations)

At NSA Data Science is a broad field, and a team effort, spanning all the expertise needed to derive value from data. As a Data Scientist specializing in Data Engineering, you will help devise and implement data systems that keep NSA at the cutting edge of intelligence gathering and reporting, with all the high-functioning supporting processes that it requires. Responsibilities include: - Working with mission owners to design, develop, and deploy new architectures for ML and automation applications such as ELT functions, HPC/compute infrastructure, AWS/Azure solutions, database solutions, and optimization of DevOps procedures - Leveraging skills in modern data architecture, cloud engineering, data transformation, and management of structured and unstructured data sources - Supporting and enhancing data architectures and data pipelines, and defining database schemas (Graph DB, SQL, NoSQL) to support algorithm scalability and deployment based on organizational priorities and technology initiatives - Participating in architectural discussions to ensure solutions are designed for successful deployment, security, and high availability - Adopting and maintaining best engineering practices in automation, HPC, CI/CD, and AI Ops

Job Summary

Depending on the skill-sets currently in demand, newly hired Data Engineers may be assigned to a mission office, or alternatively enrolled in the three-year Data Science Development Program (DSDP) in which they will both broaden and specialize their data science skills by taking courses and touring with a variety of mission offices (each for several months). In either case you will work with NSA experts in data engineering, 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.

Qualifications

Applicants will be asked to complete the Data Science Examination (DSE) evaluating 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 will be requested prior to being invited to interview with Agency data science professionals. The qualifications listed below are the minimum acceptable to be considered for the position. Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines (i.e., behavioral, social, library, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 200 level or higher; such as calculus, differential equations, discrete mathematics, linear algebra, and calculus based statistics) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper level math courses designated as elementary or basic do not count. Note: Degrees in related fields will be considered if accompanied by a Certificate in Data Science from an accredited college/university. Relevant experience must be in one or more of the following (for Entry level) but in two or more for Full Performance, Senior, and Expert levels: designing/implementing machine learning, data mining, advanced analytical algorithms, programming, data science, advanced statistical analysis, artificial intelligence, computational science, software engineering, or data engineering. ENTRY/DEVELOPMENTAL Entry is with a Bachelor's degree and no experience. An Associate's degree plus 2 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position. FULL PERFORMANCE Entry is with 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. An Associate's degree plus 5 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position. SENIOR Entry is with 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. An Associate's degree plus 8 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position. EXPERT Entry is with 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. An Associate's degree plus 11 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.

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 Knowledge, skills, and relevant experience in one or more of the following is required: - Designing and implementing machine learning - Data mining - Advanced analytical algorithms - Programming - Data science - Advanced statistical analysis - Artificial Intelligence - Computational science - Software engineering - Data engineering