Senior Data Scientist (Clearance Required)

Responsibilities

• Design, train, validate, and deploy machine learning models against Army data, from problem framing through production monitoring.
• Build production-caliber code and data pipelines that run on LMI platforms and within the customer’s environment.
• Translate ambiguous mission needs into well-scoped analytic problems, and translate model outputs into clear recommendations for Army decision-makers.
• Engineer features and data workflows across structured and unstructured sources; perform ETL, data quality assessment, and exploratory analysis to support modeling.
• Partner with software, platform, and DevSecOps engineers to integrate models into deployed systems, including evaluation, retraining, and drift monitoring after fielding.
• Apply MLOps practices (versioning, testing, CI/CD, reproducibility) to ensure models are auditable and meet federal security standards.
• Communicate methods, assumptions, and results clearly to both technical teams and senior, non-technical Army stakeholders.
• Mentor mid-level data scientists and analysts, and help set technical direction and standards for the team.

Requirements

• Active Secret clearance (or eligibility to obtain one); U.S. citizenship required.
• Bachelor’s degree in a quantitative field (computer science, statistics, mathematics, engineering, operations research, or related); advanced degree preferred.
• 7+ years of combined experience in data science, statistical modeling, analytics, or data engineering.
• Strong programming skills in Python and/or R, and SQL.
• Demonstrated experience across the analytic and ML lifecycle, including data preparation, feature engineering, modeling, and validation.
• Proven ability to communicate complex results clearly to senior decision-makers.

Preferred Experience

• Supporting Army or broader DoD customers and familiarity with operating in classified environments.
• Experience building, deploying, or maintaining models or data products in production environments, including monitoring and retraining.
• Familiarity with common ML libraries (e.g., scikit-learn, PyTorch, TensorFlow) and with MLOps practices, feature stores, or model governance.
• Experience with data pipelines and ETL (eagle streaming or event-driven processing) and with cloud environments (AWS, Azure, or GCP) and containerized workflows (Docker, Kubernetes), or willingness to develop these skills.
• Background in NLP, computer vision, time-series forecasting, anomaly detection, or operations research applied to defense problems.
• Experience with Agile delivery and working on balanced, cross-functional product teams.

Qualifications

• Target salary range: $113,560 - $192,050.