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Booz Allen Hamilton

Data Scientist, Mid

Posted 3 Days Ago
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In-Office
Springfield, VA
78K-176K Annually
Mid level
In-Office
Springfield, VA
78K-176K Annually
Mid level
Design, build, validate, and deploy AI/ML analytics for space and multi‑INT mission data. Develop anomaly detection, feature engineering, model training, and multi‑INT fusion workflows. Integrate models into cloud‑native production environments, document methods and CONOPs, collaborate with operators and government partners, and mentor junior analysts.
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Data Scientist, Mid

The 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 with cloud‑native ML platforms such as AWS SageMaker or Azure ML
  • 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
  • Active TS/SCI clearance; willingness to take a polygraph exam
  • 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
  • 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; TS/SCI clearance is required.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

  • 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

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

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