Remote Data Scientist – Interpretable Scoring

Bigbear.ai; McLean (VA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

BigBear.ai is seeking a Data Scientist to design and build v1 rule-weighted scoring logic turning risk signals into explainable scores. You will shape the architecture for future ML-based scoring with auditability in mind.

The role is fully remote with potential DMV-area travel; requires Top Secret clearance and 8–10 years of applied data science experience in scoring or decision-support models.

Qualifications

• Active Top Secret security clearance
• 8–10 years of applied data science experience
• Experience delivering scoring/ranking models with interpretability

Responsibilities

• Build v1 rule-weighted scoring logic from risk signals.
• Define scoring framework components and guardrails.
• Create interpretable explanations for scores and drivers.
• Design architecture to evolve to interpretable ML models.
• Prototype interpretable models (SHAP, monotonic models).
• Collaborate with data engineering to productionize scoring.
• Establish validation, monitoring, and QA for scores.
• Document methodology for audits and compliance.

Skills

Python

scikit-learn

SQL

Explainability

Stakeholder comms

Data visualization

Education

Bachelor's degree in quantitative field

Master's degree preferred

Tools

SHAP

Scikit-learn

Job description

BigBear.ai is seeking a Data Scientist to design and build v1 rule-weighted scoring logic turning risk signals into explainable scores. You will shape the architecture for future ML-based scoring with auditability in mind.

The role is fully remote with potential DMV-area travel; requires Top Secret clearance and 8–10 years of applied data science experience in scoring or decision-support models.