Senior Data Scientist – Simulation / Optimization

About the role

The Senior Data Scientist – Simulation / Optimization will lead the development of advanced decision intelligence systems that integrate simulation, optimization, predictive modeling, and AI capabilities across enterprise platforms. They will define and execute technical roadmaps for AI initiatives, applying advanced simulation and optimization methodologies, and serving as the primary technical leader on complex AI, machine learning, and data science initiatives.

Responsibilities

• Lead the development of advanced decision intelligence systems that integrate simulation, optimization, predictive modeling, and AI capabilities across enterprise platforms.
• Define and execute technical roadmaps for AI initiatives, translating complex business and mission challenges into scalable research and product solutions.
• Apply advanced simulation and optimization methodologies, including Discrete Event Simulation (DES), Monte Carlo methods, agent-based modeling, stochastic optimization, Bayesian optimization, and causal modeling.
• Serve as the primary technical leader and individual contributor on complex AI, machine learning, and data science initiatives from concept through production deployment.
• Design, develop, and deploy scalable AI solutions leveraging modern techniques including LLMs, agentic AI systems, multimodal AI, and advanced decision science methodologies.
• Collaborate closely with AI Research, Data Engineering, Software Engineering, Product, and Forward-Deployed teams to ensure successful implementation and commercialization of AI capabilities.
• Establish software architecture standards, technical roadmaps, and best practices for enterprise-scale AI systems.
• Mentor and develop data scientists, AI engineers, and technical team members while fostering a culture of innovation, experimentation, and technical excellence.
• Champion emerging AI technologies and continuously evaluate advancements in agentic systems, simulation, optimization, and large language models.
• Translate complex technical concepts into business and mission outcomes for executive stakeholders and clients.

Requirements

• Education: Bachelor's degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Operations Research, Engineering, or a related quantitative discipline. Advanced degree (Master's or PhD) strongly preferred.
• Experience: Minimum of 7 years of professional experience as a Data Scientist in an industry setting. Proven experience leading large-scale AI, machine learning, or advanced analytics initiatives. Experience overseeing the full lifecycle of AI projects from ideation through production deployment.
• Skills: Deep expertise in Artificial Intelligence, Machine Learning, and Data Science. Strong experience with Discrete Event Simulation (DES), Monte Carlo simulation, agent-based modeling, and stochastic optimization. Expertise in Bayesian optimization, causal discovery, and causal modeling. Experience designing and deploying agentic AI systems and AI orchestration frameworks. Strong knowledge of LLMs, multimodal AI, reasoning systems, and AI platform architecture. Experience delivering production-ready AI solutions integrated with enterprise data platforms. Strong software development and Python programming capabilities. Ability to define technical architecture and drive cross-functional execution.

Qualifications

• U.S. Citizenship is required.
• Ability to work onsite in Pittsburgh, Pennsylvania. Up to 10% travel may be required.
• Strong communication and stakeholder management skills.

Preferred Qualifications

• PhD or advanced research background in Artificial Intelligence, Machine Learning, NLP, Decision Science, Operations Research, Statistics, or related disciplines.
• Strong publication record in top-tier AI, Machine Learning, NLP, or Decision Science conferences.
• Experience building and evaluating Large Language Models and agentic AI systems.
• Experience with LLM fine-tuning, post-training, and evaluation frameworks.
• Experience transitioning research prototypes into enterprise-scale production systems.
• Experience with MLOps practices, cloud-native deployments, and large-scale model monitoring.
• Demonstrated national security, defense, or government domain expertise.
• Experience leveraging AI coding tools and AI-assisted development platforms to accelerate engineering productivity.

Benefits

• Competitive Salary: Competitive compensation package including base salary, performance incentives, and long-term growth opportunities.
• Health and Wellness: Comprehensive medical, dental, and vision coverage.
• Work-Life Balance: Paid time off, holidays, and employee wellness programs.
• Professional Development: Ongoing learning opportunities, technical training, mentorship, and exposure to cutting-edge AI technologies.
• Additional Perks: Opportunity to work on mission-critical national security initiatives while helping shape the future of AI-driven decision intelligence.