Lead Data Scientist - Simulation / Optimization
New
A
AirDefense / AI
Arlington, Virginia, United States; Pittsburgh, Pennsylvania, United States; RemoteFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- Minimum of 7 years of professional experience working as a Data Scientist in an industry setting
- Required Skills
- Artificial IntelligenceMachine LearningSoftware ArchitectureData science
Requirements
- Minimum of 7 years of professional experience working as a Data Scientist in an industry setting.
- Deep knowledge and application of discrete event simulation (DES), agent-based modeling, and Monte Carlo methods.
- Deep understanding and application of advanced optimization techniques, specifically stochastic optimization.
- Experience with Bayesian optimization, causal discovery, and causal modeling.
- Proven experience overseeing the full lifecycle of large-scale AI projects from ideation to production.
- Ability to define robust software architecture for large-scale AI systems.
- Experience with AI orchestrators, agentic systems, and coding AI tools.
- Strong technical leadership and mentorship skills.
- Excellent oral and written communication skills.
- Ability to translate complex AI concepts for both technical and non-technical audiences.
Responsibilities
- Drive the development of a complex, multi-modal decision intelligence system, serving as the central nervous architecture for integrating advanced simulation, optimization, and predictive modeling capabilities.
- Define the multi-year technical roadmap for AI initiatives, turning vague business challenges into concrete, scalable research and product goals.
- Mentor Senior-level engineers and build high-performing teams that deliver state-of-the-art results.
- Drive consensus across groups such as DS, AI, Product, and Engineering to ensure technically sound and commercially viable deployments.
- Lead the end-to-end execution of large-scale AI projects, ensuring alignment with strategic objectives and timely delivery.
- Apply deep knowledge in advanced simulation and optimization techniques, including Discrete Event Simulation, Monte Carlo methods, and stochastic optimization.
- Collaborate with Product teams to define product scope and translate high-level requirements into actionable technical plans.
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