Senior Data Scientist - Simulation / Optimization

Role overview

Lead hands-on data science and AI work focused on simulation, optimization, and decision support for complex government and national security problems. The role combines technical direction with development and deployment of analytical capabilities, helping turn varied datasets into useful insights and production systems. It also involves shaping a longer-term technical roadmap and guiding collaboration among data science, AI, product, and engineering teams.

Responsibilities - Lead end-to-end AI projects, from framing ambiguous needs and research through deployment and alignment with strategic goals. - Develop decision-support capabilities that combine simulation, optimization, and predictive modeling. - Apply modeling and optimization methods to complex capability planning and related operational problems. - Set technical direction for AI initiatives, architecture, data ecosystems, and scalable platforms. - Coordinate across research, data engineering, software development, product, and customer-facing teams to deliver practical solutions. - Mentor senior technical staff and help raise the quality and consistency of team delivery.

Requirements - U.S. citizenship and at least 7 years of professional data science experience in industry. - Practical experience with discrete-event simulation, agent-based modeling, and Monte Carlo methods. - Strong applied knowledge of stochastic optimization, Bayesian optimization, causal discovery, and causal modeling. - Ability to translate high-level problems into technical plans, robust architectures, and deployed AI solutions. - Experience collaborating across technical disciplines and communicating complex concepts to technical and non-technical audiences. - Ability to use AI coding tools to support team delivery and to apply detailed knowledge of AI systems when designing tailored solutions.

Nice to have

A strong publication record in AI, machine learning, NLP, or decision science; experience evaluating LLMs or agentic systems, fine-tuning models, or applying MLOps in cloud environments; and a record of moving research prototypes into production-grade enterprise systems. National security domain knowledge is also valued.

Benefits and work setup

The role is full-time, based in Pittsburgh, Pennsylvania, or open to remote work. Travel may reach 10%.