Manager Data Science, GenAI

AIG Insurance • Atlanta, GA

2d • Onsite

About The Position

Be part of something groundbreaking. At AIG, we are making long-term investments in a brand-new, innovative Generative AI team, designed to explore new possibilities for how artificial intelligence can be applied in insurance and beyond, and we need your help. With the support and investment needed to explore new frontiers in generative AI, you’ll be working alongside talented colleagues, innovating and leading projects that will transform how we manage risk and serve our customers. This team is central to our vision of the future and the core of our business offering. We will incorporate best-in-class engineering and product management principles and your guidance and collaboration will be critical to its success. To rapidly advance and innovate, we need your skills and expertise to build and scale world-class products. If you’re excited by the opportunity to create meaningful impact, we’d love to hear from you. Who we are: AIG is a leading global insurance organization providing a wide range of property casualty insurance and other financial services. We provide world-class products and expertise to businesses and individuals in approximately 190 countries and jurisdictions. At AIG, we’re reshaping how the world manages risk, and we’re inviting you to be a key part of that transformation. How you will create impact: As a Manager of Data Science at AIG, you will play a critical role in building and overseeing a team of data scientists tasked with delivering impactful, enterprise-level generative AI solutions. We are an applied data science team operating in an agile, production-oriented environment, and we are seeking someone with extensive hands-on experience. Candidates with only managerial or architecture backgrounds should not apply.

Requirements

• 7+ years of experience in a data science role—preferably in NLP—in an agile, production-oriented environment.
• 3+ years of experience managing teams of data scientists and/or engineers.
• 2+ years of hands-on experience building generative AI solutions: prompt engineering, RAG and agentic frameworks, validation pipelines, and observability and monitoring solutions.
• Ph.D. or Master's in Data Science, Computer Science, or a related field.
• Ability to thrive in a fast-paced, high-stakes environment.
• Clear communicator and effective collaborator within and across teams.
• Able to operate as both a hands-on practitioner and a people manager.
• Highly technical, with a strong bias for execution.

Nice To Haves

• Experience on the Palantir platform or demonstrated certification is preferred.
• Ontology Mastery: A strong understanding of Ontology —specifically how to map complex real-world data entities and relationships into a digital twin framework to power AI applications.
• Large-scale Data Infrastructure: Strong understanding of performance optimization in big data environments, with hands-on experience using distributed data processing frameworks such as Apache Spark or PySpark.
• Agentic Solution: Experience implementing advanced agentic architectures, such as autonomous agents capable of multi-step reasoning and decision-making or integrating agentic solutions with large-scale enterprise systems.

Responsibilities

• Oversee the development and delivery of data science and generative AI solutions aligned with business requirements, monitor solutions in production.
• Develop technical delivery plans and execute them to ship solutions on time.
• Mentor and develop junior data scientists.
• Collaborate with cross-functional teams including product managers, engineers, and business leaders.
• Build evaluation frameworks to measure LLM effectiveness, ground-truth dataset quality, and guide the product development roadmap.

Benefits

• Total Rewards Program, a comprehensive benefits package that extends beyond time spent at work to offer benefits focused on your health, wellbeing and financial security—as well as your professional development

What This Job Offers

• Job Type: Full-time
• Career Level: Manager