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
