Senior​/Principal Data Scientist, GenAI

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.

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.

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.

As a Data Scientist at AIG, you will serve a critical role in the architecture, development, and delivery of impactful enterprise‑level Generative AI solutions. We are seeking a highly technical individual contributor with extensive hands‑on experience, as we are an applied data science team operating in an agile and production‑oriented environment. You will be focused on Large Language Models (LLMs) and Machine Learning (ML), acting as a primary technical driver for our most complex projects.

• End‑to‑End Development:
  Lead the development and successful delivery of data science and generative AI solutions in accordance with business requirements.
• Production Oversight:
  Monitor solutions in production to ensure performance, reliability, and accuracy.
• Technical
  
  Collaboration:
  
  Partner with cross‑functional teams including product managers, engineers, and business leaders to translate requirements into technical reality.
• Evaluation & Quality:
  Build robust evaluation frameworks to measure LLM efficacy, manage ground truth dataset quality, and guide the product development roadmap.
• Architecture:
  Design scalable ML pipelines and RAG frameworks that integrate seamlessly with enterprise data structures.

• 8+ years of Engineering Experience in a development environment
• 6+ years of experience in a data science role, with a strong emphasis on NLP and ML, working in an agile production‑oriented environment.
• 3+ years of practical experience with open‑source Large Language Models (Llama 3, Mixtral, etc.), including prompt engineering, inference optimization, and fine‑tuning.
• 3+ years of experience building Generative AI Solutions, including designing and building RAG frameworks, validation pipelines, observability, and monitoring solutions.
• Proven Delivery:
  Experience successfully delivering multiple GenAI, analytical, or ML projects from conception through to production.
• Python Expertise:
  Strong, expert‑level proficiency in Python and its data science ecosystem (e.g., PyTorch, Pandas, Scikit‑learn).
• Education:
  
  Master’s degree in data science, Computer Science, or a related quantitative field.

• Palantir Platform
  
  Experience:
  
  Hands‑on experience or certification in the Palantir platform (Foundry/AIP).
• 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…