Senior Data Scientist - GenAI

The Company
Cover Genius is a Series E insurtech that protects the global customers of the world’s largest digital companies including Booking Holdings, owner of Priceline, Kayak and , Intuit, Uber, Hopper, Ryanair, Turkish Airlines, Descartes Ship Rush, Zip and Seat Geek. We’re also available at Amazon, Flipkart, eBay, Wayfair and SE Asia’s largest company, Shopee. Our partners integrate with XCover, our award‑winning insurance distribution platform, to embed protection for millions of customers worldwide each year.

Our team and products have been recognized with dozens of awards including by the Financial Times which ranked Cover Genius as the #1 fastest‑growing company in APAC in 2020. Our diverse team across 20+ countries and many language groups commit itself to diverse cultural programs, in particular “CG Gives” which makes social entrepreneurs out of us all and funds development initiatives in global communities.

Our People are Bold, Authentic, Purposeful and Inspired

Our People are not Perfect, Traditional, Complacent or Cautious

As the Senior Data Scientist for Generative AI within our Central AI Hub, you will be the foundational scientific owner of our LLM strategy. You are not just calling APIs; you are deeply involved in evaluating model performance, fine‑tuning open‑source or proprietary models for complex business logic, and ensuring our AI products behave predictably  drive success in this role, you must be a pioneer in the rapidly evolving GenAI landscape.

You will take ownership of solving complex NLP problems by bringing rigorous scientific measurement to prompt engineering and model training. You will collaborate heavily with our product and engineering teams, guiding them on how to best structure data schemas for LLM consumption, how to fine‑tune for edge cases, and how to measure success.

• Design and implement robust frameworks to quantitatively evaluate LLM performance (accuracy, repeatability, hallucination rates) before and after deployment.
• Lead the fine‑tuning and optimization of our Core Policy Models.
• Act as the central GenAI expert for product engineering teams. Guide them on improving JSON payload structures, advanced prompt engineering techniques, RAG (Retrieval‑Augmented Generation) architectures, and evaluation pipelines.
• Establish best practices, playbooks, and standardized pipelines for all AI/LLM integrations across Cover Genius.
• Stay at the cutting edge of Generative AI research, actively identifying new models, tools, and methodologies that can improve our operational efficiency and product offerings.

• Master’s or PhD in Physics, Statistics, Mathematics, Computer Science, or other Quantitative fields.
• 5+ years of practical, hands‑on ML/Data Science experience, with a heavy emphasis on NLP and at least 1‑2 years dedicated to deep Generative AI/LLM applications.
• Hands‑on experience with LLM orchestration frameworks, RAG architectures, and model fine‑tuning techniques.
• Deep understanding of how to measure generative text performance (e.g., LLM‑as‑a‑judge, traditional NLP metrics like BLEU/ROUGE, custom programmatic evaluators).
• Strong foundation in validating AI‑driven features, ensuring thresholds are statistically sound to prevent surfacing noise, and integrating human‑in‑the‑loop feedback mechanisms.
• Advanced proficiency in Python and SQL. Experience working with major LLM APIs as well as open‑weights models.
• Ability to closely collaborate with software engineers to optimize data structures (like JSON schemas) for better LLM parsing and repeatability.

• Exceptional problem‑solving skills with a high tolerance for ambiguity in the fast‑paced GenAI landscape.
• Outstanding communication skills, capable of explaining the nuances of LLM behavior to both technical and non‑technical stakeholders.
• A proactive mindset in identifying areas where “random LLM implementations” can be standardized into a robust, centralized service.

• Flexible PTO. Taking time out is important for our teams to enjoy life and stay fresh.
• Employee Stock Options – we want our people to share in our success,…