Forward Deployed Data Scientist

Air is the leader in Enterprise Readiness. Our mission is to establish readiness as a real-time condition that is continuously achieved. Today, a dangerous Readiness Gap exists between what the front line needs and what is delivered. Our AI-native platform, Air Enterprise Readiness, aligns development, production, delivery, and sustainment into one coordinated execution system for government agencies and industrial suppliers. By revealing true capacity, exposing real constraints, coordinating resources, and executing at the speed of operational demands, the front line gets what it needs to succeed.

About the role

We are seeking an inquisitive Data Scientist to join our team, leveraging deep expertise in Artificial Intelligence and a keen understanding of complex Defense Acquisition challenges. Your primary focus will be to work with our proprietary and commercial datasets to find critical connections, derive actionable knowledge, and identify potential issues that help our government clients make more informed decisions. You will design, develop, and rapidly deploy scalable AI solutions that transform these insights into mission-critical capabilities. You will expand and grow data-driven research across Air, leading new areas to apply advanced analytics to drive strategic business and national security results.

This role is a full-time position located in Arlington, VA, Pittsburgh, PA, or remote. It may require up to 50% travel.

Responsibilities

• Develop new AI methods and use existing ones to solve complex defense problems
• Develop working AI systems and deploy them
• Rapidly prototype AI models, systems, heuristics, and agentic solutions
• Work directly with customers to understand and solve their problems
• Translate customer problem definitions into technical requirements for AI-based systems
• Translate vague customer needs into concrete AI workflows and data science solutions
• Evaluate solution effectiveness with customers, tune, and redefine solutions when needed
• Deploy code into production AI systems
• Take end-to-end ownership of client problems
• Communicate clearly with both non-technical and technical users
• Work with AI platform, agentic AI, and data engineering teams to build end-to-end solutions in production deployments
• Collaborate with AI platform and agentic AI teams to generalize capabilities into reusable agentic AI features/skills for other deployments
• Wrap AI/DS solutions into AI agentic/skills frameworks
• Create agentic AI systems, using AI orchestrators and particular AI reasoning capabilities as tools

Requirements

• U.S. Citizenship is required

Skills

• Ability to translate customer problems into technical AI requirements and document them for use by multiple teams
• Deep ability to embed with clients, understand vague business or national security challenges, and translate these into concrete, actionable technical requirements and detailed documentation for AI-based systems
• Expertise in rapidly prototyping models, heuristics, and agentic solutions
• Ability to translate vague needs into concrete AI workflows and data science solutions, followed by deploying production-grade code and taking end-to-end ownership of the client's problem
• Skill in defining concrete AI workflows from vague requirements
• Experience evaluating and tuning AI solutions for effectiveness and measuring their impact
• Competency in deploying code into production AI systems
• Competency in building agents/skills solving particular problems
• Expertise in integrating AI/DS solutions into agentic frameworks
• End-to-end ownership of client problems
• Strong communication with non-technical and technical users
• Collaboration with cross-functional teams for production deployment
• Strong collaboration and communication skills to work effectively with AI platform and data engineering teams, including generalizing unique AI/DS solutions into reusable agentic features/skills

Desired Skills

• A strong publication record in top conferences in AI, ML, NLP, or decision science
• Deep knowledge of LLM and agentic system evaluation, experience in building evaluation systems
• Extensive expertise in specialized domains such as Operations Research, Optimization, and Decision Science
• Track record of successfully transitioning AI research prototypes into robust, production-grade enterprise solutions