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Sr. Data Scientist

Job in Fort Meade, Anne Arundel County, Maryland, USA
Listing for: Themisinsight
Full Time position
Listed on 2025-12-20
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Machine Learning/ ML Engineer, Data Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Overview

Themis Insight solves difficult business, IT, and analytic problems by addressing the whole problem – not just the symptoms – using interdisciplinary approaches that are both practical and innovative. We provide fresh alternatives to ordinary, mainstream consulting firms through small, highly skilled, and hand‑picked teams that can meet clients' needs in any industry. Our broad interdisciplinary understanding allows us to provide the right solution, even if it is from outside the industry or traditionally defined problem space.

We bring Public and Private, Civilian and Military expertise to every case.

We are hiring a Sr. Data Scientist to work in Fort Meade, MD. Position location is subject to change based on central MD client's needs.

Required: TS/SCI with a Polygraph

Responsibilities

Employ some combination (2 or more) of the following skill areas:

  • Foundations:
    Mathematical, Computational, Statistical
  • Data Processing:
    Data management and curation, data description and visualization, workflow and reproducibility
  • Modeling, Inference, and Prediction:
    Data modeling and assessment, domain-specific considerations
  • Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge. Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in NSA/CSS data holdings.

    Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly‑shifting NSA/CSS collection, processing, storage and analytic capabilities and limitations.

    Qualifications

    Individual Capabilities/Experience

    Required:

    • A Bachelor’s degree and 10 years of relevant experience. An Associate’s degree plus 12 years of relevant experience may be considered for individuals with in‑depth experience that is clearly related to 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, social, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 300 level or higher;

      such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses designated as elementary or basic do not count.
    • Note:

      A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
    • Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high‑level language (e.g. Python) and skill in at least one mid‑level language (e.g.

      C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support a single or multiple domain areas, and/or software engineering.

      Experience in more than…
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