Air (formerly Govini)
Lead Data Scientist
Pittsburgh, PA · On-site · Senior
- Discipline
- Software
- Industry
- Defense
- Constraints
- U.S. person required
Spec sheet
Automatically summarized from the employer’s posting. Check the original description below for full requirements.
AI
Data Science leader at Air in the U.S. offices (Arlington, VA / Pittsburgh, PA / San Francisco, CA) to direct core AI and data science work. You will own end-to-end DS lifecycle and drive cross-functional initiatives across DS, AI, data engineering, and product teams.
10% travel · 7+ years
Required
- 7+ years of experience in Data Science or Applied AI
- lead large-scale Data Science initiatives
- end-to-end data science lifecycle
- ability to lead cross-functional initiatives
- strong technical leadership and communication
- experience with AI system architectures
- experience with AI-assisted software development tools
- ability to mentor Data Scientists
Preferred
- US security clearance (desired)
- startup experience
- scaling reusable DS capabilities
- agentic AI systems design
- foundation model adaptation
- robust experimentation frameworks
- experience with defense/government datasets
Employer description
Company Description
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.Job Description
We are seeking an exceptional Data Science leader to technically lead and own major areas of Air’s core AI and Data Science, advancing the modeling, algorithms, and scientific foundations that power our products, including the data science behind Enterprise Readiness. This role will develop foundational AI capabilities that become core building blocks of Air’s products and can be leveraged by Forward Deployed Data Science teams across dozens of deployments and clients.
This leader will set the strategic direction for Core Data Science and Applied AI, identify and prioritize high-impact technical opportunities, and drive the development of reusable modeling capabilities. The role will own the end-to-end Data Science lifecycle, from problem formulation and model development and training through evaluation and validation in real-world, end-to-end use cases. We are seeking a leader who can combine deep technical expertise with strong organizational leadership to build a high-impact core science function and translate advanced Data Science into capabilities that scale across the company.
In order to do this job well, you should have a broad foundation across Data Science and deep expertise in one or more core areas such as optimization, simulation, forecasting, reinforcement learning, causal inference, or foundation modeling. You should be able to lead large-scale Data Science initiatives end to end, from identifying opportunities and working directly with clients, through partnering with Forward Deployed Data Science teams to understand their needs, to model development, evaluation, and deployment aligned with client outcomes. You should be comfortable leading cross-functional efforts spanning Data Science, platforms, Agentic AI, and data engineering, bringing together diverse technical disciplines to solve complex problems. You will also drive the scientific roadmap for the areas you own, establish technical direction and best practices, and mentor and develop other Data Scientists to build deep expertise and advance the organization’s scientific capabilities.
This role is a full-time position located out of our office in Arlington, VA / Pittsburgh, PA / San Francisco, CA.This role may require up to 10% travel
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.
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