Mid-Level Data Scientist (TS/SCI)
Honolulu, Hawaii, US
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingBuild, 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 qualificationsCore 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
All applicants must currently reside in the United States
Overview
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on careers-bigbearai.icims.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Honolulu, Hawaii, US
Working pattern and location restrictions need checking in the full posting.
- 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
- Active
- First seen by us
- Sep 10, 2026
- Recorded sightings
- 88
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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