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Data Scientist IV

Black Eagle Defense

Posted today

Job Requirements

Fort Meade, MD
Top Secret/SCI Full Scope Polygraph
Career Level not specified
$190,000 - $247,000

Job Description

Job Description

SALARY RANGE $190,000 - $247,000/year

DUTIES As a successful candidate for the Data Scientist IV role, you will devise strategies for extracting meaning and value from large datasets and serve as an established AI expert with demonstrable experience designing and implementing sophisticated AI/ML and data science solutions across various domains within the MPO customer environment. You will 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 other appropriate scientific methods, you will develop and implement qualitative and quantitative approaches for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure, accounting for the unique features and limitations inherent in NSA/CSS data holdings. You will design and implement Agentic AI systems and customized Retrieval Augmented Generation (RAG) capabilities, assess and select appropriate machine learning models for specific mission purposes, and optimize model performance across constrained environments. You will generate, evaluate, train, and optimize machine learning models, including large language models (LLMs), for deployment in low-memory, low-resource edge device environments. You will translate practical mission needs and analytic questions into technical requirements, assist others in drawing appropriate conclusions from analytical results, effectively communicate complex technical information to non-technical audiences, and make informed recommendations regarding competing technical solutions by maintaining awareness of evolving NSA/CSS collection, processing, storage, and analytic capabilities and limitations.

Required Skills

SKILLS 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, AI/ML model selection and optimization)


  • QUALIFICATIONS

    Education and Experience
    • Bachelor's degree with 15 years of relevant experience, or
    • Associate's degree with 17 years of relevant experience
    • Experience must be in-depth and clearly related to the position


    Degree Requirements
    • Bachelor's degree in one of the following:
      • Mathematics
      • Applied Mathematics
      • Statistics or Applied Statistics
      • Machine Learning
      • Data Science
      • Operations Research
      • Computer Science
    • Related degrees may be considered, including:
      • Computer Information Systems
      • Engineering
    • Physical or hard science degrees (e.g., physics, chemistry, biology, astronomy) or other science disciplines may be considered if they include a substantial computational component and at least five advanced (300-level or higher) courses in:
      • Mathematics (e.g., linear algebra, probability, statistics, machine learning), and/or
      • Computer Science (e.g., algorithms, programming, data structures, data mining, artificial intelligence)


    Additional Degree Considerations
    • College-level requirements or upper-level math courses designated as elementary or basic do not count
    • A broader range of degrees may be considered if accompanied by a Certificate in Data Science from an accredited college or university


    Required Experience Areas

    Relevant experience must include work in the following areas:
    • Designing and implementing machine learning and AI solutions
    • Data science
    • Advanced analytical algorithms
    • Programming in at least one high-level language (e.g., Python)
    • Statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, exploratory data analysis, linear models)
    • Data management (e.g., data cleaning and transformation)
    • Data mining
    • Data modeling and assessment
    • Artificial intelligence
    • Software engineering

    Experience spanning more than five of the areas listed above is strongly preferred

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