Lead Data Scientist

Company Description

Job Description

Scope of Responsibilities 

• Lead Core Data Science Strategy: Define and drive the technical roadmap for core Data Science capabilities, translating complex client and business challenges into scalable data science and Applied AI across the Air Enterprise readiness .
• Set Scientific Standards and Drive Innovation: Establish best practices for model architecture, experimentation, evaluation, and deployment; assess emerging research and technologies; and translate scientific advances into robust, cost-effective, production-ready capabilities.
• Advance Core Modeling Capabilities: Drive the development of state-of-the-art methods across specialized areas such as simulation, optimization, forecasting, predictive modeling, reinforcement learning, and foundation models, applying deep expertise in one or more domains.
• Own End-to-End Scientific Execution: Lead large-scale Data Science projects from problem formulation and ideation through model development, training, evaluation, and production deployment, ensuring solutions deliver measurable client impact.
• Build Scalable Decision Intelligence Platforms: Working together with the MLOps team, guide the development of reusable modeling capabilities that integrate with data platforms, Agentic AI systems, and client workflows to power complex decision intelligence solutions across diverse defense use cases.
• Drive Cross-Functional Technical Leadership: Align Data Science, Applied AI, Forward Deployed Data Science, Product, Platform, and Engineering teams on scientific priorities, technical architecture, project execution, and evaluation criteria tied to client and product objectives.
• Develop Talent and Organizational Excellence: Mentor and develop Data Scientists across experience levels, foster deep expertise in core scientific disciplines, and cultivate a culture of technical excellence, rigorous experimentation, knowledge sharing, and continuous learning.

Qualifications

• U.S. Citizenship is required

• 7+ years of experience in Data Science or Applied AI, with a proven track record of leading large-scale, company-wide Data Science initiatives from ideation to production and delivering significant impact on products and business outcomes.
• Broad understanding of Data Science foundations, with deep expertise in one or more core areas such as optimization, simulation, reinforcement learning, forecasting, causal inference, computer vision, natural language processing, decision science, or foundation model training.
• Proven ability to lead complex Data Science projects end to end, define scientific roadmaps, establish technical direction, and drive execution from problem formulation and model development through evaluation and production deployment.
• Strong understanding of AI system architectures and internals, including agentic systems, with the ability to design and implement customized, scalable, and highly optimized solutions.
• Experience with AI-assisted software development tools such as Claude Code to accelerate development, improve engineering productivity, and scale the delivery capacity of Data Science and Applied AI teams.
• Demonstrated ability to lead cross-functional initiatives involving Data Science, AI Research, Data Engineering, Software Engineering, Platform, and Product teams, translating product requirements into technical roadmaps, robust architectures, and production-ready solutions integrated with client data platforms and workflows.
• Strong technical leadership and communication skills, with the ability to align AI strategy with client and business needs, drive timely delivery, mentor and develop Data Scientists, and promote technical excellence, innovation, and continuous learning across the organization.
• Demonstrated ability to influence technical strategy across organizational boundaries, build alignment among senior technical and product stakeholders, and establish standards adopted across multiple teams.

Desired Skills: 

• Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship 
• Experience in or exposure to the nuances of a startup or other entrepreneurial environment
• Experience building and scaling reusable Data Science capabilities and modeling platforms that support multiple products, clients, and deployment environments.
• Experience designing and evaluating agentic AI systems, including tool use, orchestration, long-horizon execution, retrieval, and integration with specialized models and analytical tools.
• Familiarity with modern AI research and development practices, including foundation model adaptation, synthetic data generation, reinforcement learning, and systematic model evaluation.
• Experience developing robust experimentation and evaluation frameworks that measure model quality, system reliability, and impact on end-to-end client outcomes.
• Experience working with complex enterprise or government datasets, particularly in defense, logistics, supply chain, sustainment, acquisition, or other domains involving high-stakes decisions and operational constraints.