Data Scientist (TS/SCI)

Residency

All applicants must currently reside in the United States

Overview

BigBear.ai is seeking a Mid-Level Data Scientist to support a Department of the Army enterprise data team by delivering advanced analytics, predictive modeling, and secure AI/ML integration. In this role, you will apply rigorous statistical methods and modern machine learning (including NLP and Generative AI) to forecast operational trends, inform executive decisions, and develop high-fidelity models, dashboards, and cognitive agents across multiple classification enclaves.

You will collaborate closely with Data Architects and Data Engineers to build on standardized, governed data pipelines and help maintain trusted “single source of truth” repositories in accordance with strict security and classification protocols.

What you will do

Build, test, and deploy machine learning and statistical models (e.g., forecasting, classification, regression) to answer mission-critical questions and improve decision-making

Conduct exploratory data analysis (EDA) to identify trends, anomalies, data quality issues, and operational drivers across complex, multi-source datasets

Develop and operationalize features and model pipelines in partnership with data engineers, ensuring solutions are scalable, maintainable, and reproducible in secure environments

Apply NLP and modern AI techniques (including governed LLM/GenAI patterns where approved) to extract insight from unstructured text, reports, and messaging data

Create clear, executive-ready analytic products (dashboards, visualizations, and briefings) that translate technical results into actionable recommendations

Work across multiple classification enclaves while complying with all security, handling, and documentation requirements

Collaborate with stakeholders to refine problem statements, define measures of success, and validate that analytic outputs align to operational needs

Monitor and improve model performance over time, including drift detection, recalibration, and documentation of assumptions and limitations

What you need to have

5+ years of experience in applied statistics, predictive modeling, ML, or quantitative research

Active DoD TS/SCI security clearance

Demonstrated experience and proficiency working in Python, R, and SQL for analysis/modeling/EDA

Demonstrated knowledge and application of forecasting, regression, and modern ML frameworks (scikit‑learn, TensorFlow, PyTorch)

Experience working with LLMs/Generative AI within secure, governed enterprise boundaries

Experience with creating executive‑level data storytelling via visualizations/dashboards

Bachelor’s degree in a quantitative field (Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science (with strong mathematics focus); Operations Research

What we'd like you to have

Experience working within enterprise big data platforms, especially Palantir Foundry (Contour, Workshop, Quiver) or Databricks, Snowflake

Familiarity with the Defense/Intelligence sector, including Headquarters operations and intelligence data structures/sources

Experience in data cataloging/master data management and metadata practices as prerequisites for AI/ML deployment

Master’s degree in a quantitative field (Statistics, Data Science, Operations Research, Applied Mathematics, or related)

Pay transparency

Please note the targeted compensation range is provided as an estimate, and any actual compensation offer may vary depending on the needs of the company, or an applicant's skillset, competencies, experience, education, certifications, location, or other factors. The estimated range does not include the value of any benefits offered.

About BigBear.ai

BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.

BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.

Build, test, and deploy machine learning and statistical models (e.g., forecasting, classification, regression) to answer mission-critical questions and improve decision-making

Conduct exploratory data analysis (EDA) to identify trends, anomalies, data quality issues, and operational drivers across complex, multi-source datasets

Develop and operationalize features and model pipelines in partnership with data engineers, ensuring solutions are scalable, maintainable, and reproducible in secure environments

Apply NLP and modern AI techniques (including governed LLM/GenAI patterns where approved) to extract insight from unstructured text, reports, and messaging data

Create clear, executive-ready analytic products (dashboards, visualizations, and briefings) that translate technical results into actionable recommendations

Work across multiple classification enclaves while complying with all security, handling, and documentation requirements

Collaborate with stakeholders to refine problem statements, define measures of success, and validate that analytic outputs align to operational needs

Monitor and improve model performance over time, including drift detection, recalibration, and documentation of assumptions and limitations

5+ years of experience in applied statistics, predictive modeling, ML, or quantitative research

Active DoD TS/SCI security clearance

Demonstrated experience and proficiency working in Python, R, and SQL for analysis/modeling/EDA

Demonstrated knowledge and application of forecasting, regression, and modern ML frameworks (scikit‑learn, TensorFlow, PyTorch)

Experience working with LLMs/Generative AI within secure, governed enterprise boundaries

Experience with creating executive‑level data storytelling via visualizations/dashboards

Bachelor’s degree in a quantitative field (Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science (with strong mathematics focus); Operations Research