Senior Data Scientist​/Analytics Lead

Position Summary

As the Data Scientist and Analytics Lead, you will serve as the principal architect for data traceability and advanced analytics in support of the Army Materiel Command (AMC) Chief Technology Officer (CTO). In this critical advisory role, you will design the robust analytical models required to transform raw operational data into actionable leadership insights. Your work will empower enterprise senior leaders with the analytical depth and strategic frameworks necessary to make informed, defensible decisions regarding technology investments, pilot programs, and digital modernization initiatives.

You will lead the development of a comprehensive suite of enterprise‑level assessments, establishing a continuous, disciplined evaluation framework that serves as a single source of truth for the organization. By integrating advanced analytics, artificial intelligence pipelines, and operational dashboards into enterprise systems, you will create a highly traceable record of evidence that directly aligns technology initiatives with strategic mission priorities. This position is ideal for an expert who thrives on translating complex technical ecosystems into clear, executive‑ready decision support products.

• Design and implement advanced analytical models that transform raw operational and technical data into actionable leadership insights.
• Establish and maintain data traceability methodologies to ensure a disciplined linkage from source data and assumptions through to final leadership recommendations and decisions.
• Develop and integrate artificial intelligence (AI) pipelines and operational dashboards within enterprise platforms, such as Army Vantage, to provide real‑time decision support and consumption tracking.
• Define rigorous success criteria, precise data requirements, and Key Performance Indicators (KPIs) for emerging technology pilot programs before they are initiated.
• Conduct comprehensive, repeatable assessments measuring technical maturity, operational efficiency, feasibility, cyber risk, and program alignment across the technology portfolio.
• Produce high‑level executive decision support products, including formal options papers, executive memoranda, briefing decks, and recurring portfolio dashboards.
• Provide the analytical rigor required to evaluate technology sandbox initiatives and establish standardized metrics for post‑evaluation After‑Action Reviews (AARs).

• Bachelor's Degree from an accredited school in a technical discipline (e.g., data science, engineering, mathematics, science, computer science).
• Extensive proven experience functioning as a principal data architect or analyst, specifically designing models that translate complex data into executive‑level insights.
• 10+ years of relevant professional experience.
• Expertise in languages like Python, R, and SQL; data visualization software like Tableau, Power BI, or Qlik; and data management platforms like ADVANA, Palantir Foundry, Databricks, Snowflake, and Azure Synapse Analytics.
• Strong background in establishing data traceability methodologies and evidence‑based decision support frameworks for large‑scale enterprise environments.
• Experience defining operational metrics, Key Performance Indicators, and strict success criteria for technology pilots, software applications, or capability assessments.
• Exceptional ability to produce executive‑ready communication products, briefing materials, and strategic documentation for senior leadership.
• Demonstrated ability to build, deploy, and manage artificial intelligence pipelines and comprehensive operational dashboards.
• U.S. citizenship and an active Secret security clearance with the ability to obtain/maintain a Top Secret/Sensitive Compartmented Information (TS/SCI) clearance.

• Master's Degree from an accredited school in a technical discipline.
• Familiarity with the Army Materiel Command mission, including broader Department of War Supply Chain and Organic Industrial Base (OIB) operations.
• Deep understanding of assessment frameworks utilized to measure technical debt, application lifecycle health, and overall enterprise…