Bigbear.ai

Operational AI platform for decision support

Data Scientist

Data ScienceConfirmed live in the last 24 hours

Full-timeHonolulu, HI, USANo salary listedIn-person

About the Job

Requirements

At least 5 years of experience in applied statistics, predictive modeling, machine learning, or quantitative research.
An active Department of Defense Top Secret/Sensitive Compartmented Information security clearance.
Proficiency working in Python, R, and SQL for analysis, modeling, and exploratory data analysis.
Knowledge and application of forecasting, regression, and modern machine learning frameworks, including scikit-learn, TensorFlow, and PyTorch.
Experience working with large language models or generative AI within secure, governed enterprise boundaries.
Experience creating executive-level data storytelling through visualizations and dashboards.
A bachelor's degree in a quantitative field such as Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science with a strong mathematics focus; or Operations Research.
Must currently reside in the United States.

Responsibilities

Build, test, and deploy machine learning and statistical models, including forecasting, classification, and regression, to answer mission-critical questions and improve decision-making.
Conduct exploratory data analysis 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 natural language processing and modern AI techniques, including governed large language model and generative AI patterns where approved, to extract insight from unstructured text, reports, and messaging data.
Create executive-ready analytic products, including dashboards, visualizations, and briefings, that translate technical results into actionable recommendations.
Work across multiple classification enclaves while complying with security, handling, and documentation requirements.
Collaborate with stakeholders to refine problem statements, define measures of success, and validate that analytic outputs align with operational needs.
Monitor and improve model performance over time, including drift detection, recalibration, and documentation of assumptions and limitations.

Desired Qualifications

Experience working within enterprise big data platforms, especially Palantir Foundry (Contour, Workshop, and Quiver), Databricks, or Snowflake.
Familiarity with the Defense or Intelligence sector, including headquarters operations and intelligence data structures and sources.
Experience in data cataloging, master data management, and metadata practices as prerequisites for AI/ML deployment.
A master's degree in a quantitative field such as Statistics, Data Science, Operations Research, Applied Mathematics, or a related field.

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.

About the Company

Bigbear.ai

Operational AI platform for decision support

BigBear.ai builds operational AI software that helps organizations improve decision-making, cyber operations, and business agility. Its platform combines AI-driven analytics on an organization’s data with external inputs to give a full, real-time view of the environment, uncover new insights, and produce accurate predictions. The product works by integrating data from internal systems and external sources, applying advanced analytics to surface actionable intelligence, and enabling fast, informed actions in complex settings. What sets BigBear.ai apart is its depth of expertise in operational AI and its ability to optimize existing data with additional inputs, delivering data mining and predictive capabilities that go beyond traditional intelligence tools. Its goal is to help clients succeed in mission-critical environments—such as government intelligence, healthcare, and manufacturing—by improving efficiency, risk management, and operational performance.

Company size: 501-1,000
Company stage: IPO
Headquarters: Tysons, VA
Founded: 2020

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