Data Scientist - Healthcare Supply Chain Risk

Location: McLean, Virginia

Work Environment: Hybrid

Role Summary:

Exiger is seeking a Data Scientist with expertise in machine learning, NLP/LLMs, and statistical modeling to support mission-critical analytics for public sector customers. This role is ideal for an individual who thrives at the intersection of data science, supply chain risk, and operational decision-making, and can apply advanced analytics to strengthen supply chain resilience, improve risk visibility, and support continuity of operations.

The Data Scientist will develop and operationalize predictive risk models, anomaly detection systems, and supply chain analytics tools, working closely with AI Solutions Engineers and SCRM analysts to ensure seamless integration into customer environments. This individual will also design dashboards and visualizations, conduct large-scale data analysis across supplier networks and product flows, and present actionable insights to operational and leadership stakeholders—aligning advanced analytics with mission outcomes.

What You'll Do:

• Develop and apply machine learning (ML) and NLP/LLM models to support supply chain risk identification, supplier analysis, and operational decision-making.
• Build predictive risk models to identify and prioritize vulnerabilities across products, suppliers, and supply chain dependencies.
• Conduct statistical analysis on large-scale datasets (e.g., supplier data, product/SKU data, logistics and trade data) to identify anomalies, disruptions, and concentration risks.
• Design and implement risk scoring methodologies that incorporate supplier health, geographic exposure, dependency mapping, and external risk signals.
• Support scenario analysis and modeling to assess the impact of supply-side and demand-side disruptions.
• Collaborate with Forward Deployed Engineers to operationalize models within Exiger’s platform and customer workflows.
• Design and maintain dashboards, reports, and data visualizations to communicate insights to both technical and non-technical stakeholders.
• Translate complex analytical outputs into clear, mission-relevant insights for government stakeholders and operational users.
• Partner with SCRM analysts and program leadership to continuously refine models based on real-world risk signals and evolving mission priorities.

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