Booz Allen

DataScientist,Mid

$78–78k Springfield, Virginia, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data Scientist, Mid at Booz Allen. Skills: Data Science, Machine Learning, AI/ML Model Development, SQL, Python, Cloud-native ML platforms. Contribute to analytic development and mission-focused modernization across space-based GEOINT environments. Design, build, validate, and deploy analytic models”

What You'll Achieve.

Enhance decision advantage for operational users; Deliver high-quality analytics tailored for real-time and near-real-time operational use; Ensure analytics align with mission needs and timelines

Industry & Context.

Problems you'll solve

Translate mission objectives into technical requirements; Implement analytic prototypes; Ensure outputs meet mission timelines, accuracy expectations, and operational usability standards; Support the development of statistical baselines, anomaly detection workflows, and multi-INT fusion analytics

Eligibility Requirements

Active TS/SCI willingness to take a polygraph exam, TS/SCI clearance is required, Security investigation, Eligibility requirements for access to classified TS/SCI clearance

What They're Looking For.

Must 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, Active TS/SCI willingness to take a polygraph exam, HS diploma or GED

Nice to 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, Google Professional Machine Learning Engineer certification, Azure Data Scientist Associate certification, AWS Machine Learning – Specialty certification, TensorFlow Developer Certification

What You'll Do.

Contribute to analytic development and mission-focused modernization across space-based GEOINT environments

and deploy analytic models

Build end-to-end analytic workflows

Ingest complex mission data

Develop repeatable models

Deploy models into cloud-native environments

Translate mission objectives into technical requirements

Implement analytic prototypes

Ensure outputs meet mission timelines

accuracy expectations

and operational usability standards

Support the development of statistical baselines

anomaly detection workflows

and multi-INT fusion analytics

and validate analytics supporting multi-INT

and space-system data

Build and evaluate AI/ML models

Contribute to data engineering workflows

and storage of large mission datasets

Develop analytic prototypes and support their operationalization into cloud-native platforms

Integrate models and analytics into mission-critical workflows

supporting near-real-time data processing

Perform feature engineering

hyperparameter tuning

and baseline creation for anomaly detection and system-behavior characterization

Support multi-INT data fusion

or related mission data types

Document analytic methods

and validation frameworks

Contribute to technical deliverables and analytic CONOPs

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

How You'll Work.

Team & Collaboration

Work within a multi-disciplinary team of data engineers, mission analysts, and cloud engineers; Collaborate with government partners, operators, and senior data scientists; Collaborate with operators and mission partners; Collaborate in a high-tempo environment

Communication Scope

Communicate technical concepts to mission stakeholders

Full Job Description

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, includi

Free ATS check

Applying for this Data Scientist, Mid role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

How to Apply on Workday

  • Workday has a multi-step form — save your progress after every section.
  • "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
  • Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
  • Job requisition numbers are useful when following up with HR by email.

ANONYMOUS · UNFILTERED

What do employees actually say about Booz Allen?

Real rants from real employees. Read before you apply.

Read Company Rants →