Peraton's Risk Decision Group is seeking a Director of Information / Data Science to lead the RDG Data Science as a Service (DSaaS) initiative, driving the organization's transition from proof-of-concept to production-scale AI and analytics services. This role owns the strategy and execution of a scalable, cloud-native intelligence platform designed to embed AI-driven insight across all RDG operations — spanning model development and deployment, GenAI, agentic workflows, and intelligent document processing. The ideal candidate combines deep technical expertise in ML Ops and production AI systems with the cross-functional leadership needed to navigate hybrid cloud architecture, compliance, and enterprise data governance in a government contracting environment.
This is a 100% Remote position.
Responsibilities
- Lead the DSaaS initiative through phased production rollout, from initial cloud-based use cases through full hybrid cloud integration and enterprise-wide AI service delivery.
- Own and evolve the DSaaS service architecture across platform, service, feature, and user tiers — ensuring scalable, repeatable, and compliant delivery of intelligence services across RDG operations.
- Drive the ML Ops strategy, establishing standardized pipelines for model training, evaluation, deployment, and monitoring across a cloud-native, GovCloud-compliant environment.
- Support and co‑lead the data access and governance strategy in close partnership with enterprise data and cybersecurity teams, ensuring alignment across derivative, organizational, and authoritative data tiers with compliance and ATO requirements.
- Develop and deploy production-quality AI/ML models — including risk scoring, anomaly detection, intelligent document processing, and LLM/agentic solutions — that drive measurable operational improvements.
- Represent the data science team in cross-functional coordination with Cyber, Infrastructure, Compliance, and Engineering stakeholders to align on hybrid cloud architecture and enterprise data strategy.
- Champion a "Buy Over Build" philosophy — evaluating and integrating commercial platforms where possible, reserving custom development for requirements that commercial solutions cannot meet.
- Build and manage a lean, high-performing data science team; identify and advocate for dedicated engineering support in cloud infrastructure, DevOps, and platform administration required to scale.
- Evaluate emerging AI/ML technologies and identify strategic opportunities to continuously expand DSaaS capabilities and service offerings.