631 Booz Allen Hamilton_United States · Springfield, VA

Data Scientist, Mid at 631 Booz Allen Hamilton_United States — Springfield, VA

Full-timeSpringfield, VA$77,600–$176,000/yearPosted 2026-07-22Apply on Workday
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Full job description

Data Scientist, MidThe Opportunity:

As a mid‐level data scientist supporting a Space Force program, you will contribute to analytic development and mission‐focused modernization across space-based GEOINT environments. You will work within a multi‐disciplinary team of data engineers, mission analysts, and cloud engineers to design, build, validate, and deploy analytic models that enhance decision advantage for operational users.

You will help build end‐to‐end analytic workflows, from ingesting complex mission data to developing repeatable models and deploying them into cloud‐native environments. You will translate mission objectives into technical requirements, implement analytic prototypes, and ensure outputs meet mission timelines, accuracy expectations, and operational usability standards.

In this role, you will support the development of statistical baselines, anomaly detection workflows, and multi‐INT fusion analytics. You will work with tools such as Python, SQL, FADE or MIST, JEMA, and modern AI/ML libraries. You will collaborate with government partners, operators, and senior data scientists to deliver high‐quality analytics tailored for real‐time and near‐real‐time operational use.

What You’ll Do

  • Design, implement, and validate analytics supporting multi‐INT, geospatial, and space‐system data.
  • Build and evaluate AI/ML models using libraries such as TensorFlow, PyTorch, and Scikit‐learn.
  • Contribute to data engineering workflows, including ingestion, transformation, QC, and storage of large mission datasets.
  • Develop analytic prototypes and support their operationalization into cloud‐native platforms such as AWS, Azure, or hybrid government cloud.
  • Integrate models and analytics into mission‐critical workflows, supporting near‐real‐time data processing.
  • Perform feature engineering, model training, hyperparameter tuning, and baseline creation for anomaly detection and system‐behavior characterization.
  • Support multi‐INT data fusion, including GEOINT, SIGINT, MTI, ISR, or related mission data types.
  • Document analytic methods, model assumptions, performance metrics, and validation frameworks.
  • Contribute to technical deliverables and analytic CONOPs in collaboration with senior data science leadership.
  • Collaborate with operators and mission partners to ensure analytics align with mission needs and timelines.
  • Provide mentorship to junior analysts and support continuous improvement of analytic best practices.

Join us. The world can’t wait.

You Have:

  • Experience in data science, applied analytics, or ML
  • Experience working with geospatial or multi‐INT datasets, and developing and validating AI/ML models
  • Experience with distributed compute environments and handling high‐volume mission data
  • Experience integrating models or analytics into production or mission workflows
  • Experience developing queries, transformations, and operational analytics in SQL and Python
  • Ability to support analytic CONOPs, translate mission requirements, and document technical approaches
  • Ability to collaborate in a high‐tempo environment and communicate technical concepts to mission stakeholders
  • Top Secret clearance
  • HS diploma or GED

Nice If You Have:

  • Experience with IC or DoD analytics, including within DIA, CCMDs, USSPACECOM, or mission‐partner organizations
  • Experience with FADE or MIST, JEMA, or operator‐facing mission‐system analytics
  • Experience building models for MTI, ISR such as SAR and EO, or space‐domain analytics
  • Experience developing or supporting enterprise‐level data architectures, catalogs, or metadata frameworks
  • Experience with cloud‐native ML platforms such as AWS SageMaker or Azure ML
  • TS/SCI clearance with a polygraph
  • Professional Certifications such as Google Professional Machine Learning Engineer, Azure Data Scientist Associate, AWS Machine Learning – Specialty, or TensorFlow Developer Certification

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Top Secret clearance is required.

Compensation

Identity Statement

Candidate AI Usage Policy

  • Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
  • Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
  • Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination