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Mid-Level Data Scientist (TS/SCI)

Honolulu, Hawaii, US

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Apply at Bigbear.ai Holdings Inc

What you’ll work on

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

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

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

From the employer’s posting
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
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
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

What you’ll bring

All qualifications

Core experience

  • 5+ years of experience in applied statistics, predictive modeling, ML, or quantitative research
  • Bachelor’s degree in quantitative field (Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science (with strong mathematics focus); Operations Research or Econometrics)
  • 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
Qualification wording
5+ years of experience in applied statistics, predictive modeling, ML, or quantitative research
Bachelor’s degree in quantitative field (Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science (with strong mathematics focus); Operations Research or Econometrics)
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

Tools in this posting

  • Python
  • R
  • SQL
  • Databricks
  • TensorFlow
  • Snowflake
  • scikit-learn
  • PyTorch
Source — Tool mentions in context
- Bachelor’s degree in quantitative field (Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science (with strong mathematics focus); Operations Research or Econometrics) - 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)
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
- 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

About Bigbear.ai Holdings Inc

BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity.

In the employer’s words · Read in context

Job description

View original posting ↗

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

  • Must maintain an active DoD TS/SCI security clearance
  • 5+ years of experience in applied statistics, predictive modeling, ML, or quantitative research
  • Bachelor’s degree in quantitative field (Statistics, Applied Mathematics, or Physics; Electrical, Systems, Industrial, or Computer Engineering; Computer Science (with strong mathematics focus); Operations Research or Econometrics)
  • 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

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 quantitative field (Statistics, Data Science, Operations Research, OR 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.

 

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Pay

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Location & working pattern

Honolulu, Hawaii, US

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Work authorization
What you need to have - Must maintain an active DoD TS/SCI security clearance - 5+ years of experience in applied statistics, predictive modeling, ML, or quantitative research
Status in our records
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First seen by us
Sep 10, 2026
Recorded sightings
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Last seen by us
Oct 8, 2026

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