Senior Data Scientist I

About Chubb Chubb is a world leader in insurance. With operations in 54 countries and territories, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. The company is defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength and local operations globally. Parent company Chubb Limited is listed on the New York Stock Exchange (NYSE: CB) and is a component of the S&P 500 index. Chubb employs approximately 43,000 people worldwide. Additional information can be found at: www.chubb.com . About Chubb India At Chubb India, we are on an exciting journey of digital transformation driven by a commitment to engineering excellence and analytics. We are proud to share that we have been officially certified as a Great Place to Work® for the third consecutive year, a reflection of the culture at Chubb where we believe in fostering an environment where everyone can thrive, innovate, and grow. With a team of over 2500 talented professionals, we encourage a start-up mindset that promotes collaboration, diverse perspectives, and a solution-driven attitude. We are dedicated to building expertise in engineering, analytics, and automation, empowering our teams to excel in a dynamic digital landscape. We offer an environment where you will be part of an organization that is dedicated to solving real-world challenges in the insurance industry. Together, we will work to shape the future through innovation and continuous learning. Position Details: • Function/Department : Advanced Analytics • Location : Bangalore, India • Employment Type: Full-time •

– Senior Data Scientist

: AI/ML & Data Science • Develop and deploy end-to-end machine learning solutions for insurance use cases such as claims triage, fraud detection, reserve estimation, underwriting risk scoring, and subrogation identification. • Build and operationalize LLM-powered applications, including claim summarization, adjuster assistance tools (copilots), intelligent document extraction, and RAG pipelines. • Fine-tune, prompt-engineer, and adapt foundation models (e.g., GPT-4, Gemini, LLaMA) for domain-specific applications. • Design advanced NLP pipelines to extract structured insights from unstructured sources (e.g., claim notes, medical records, police reports). • Explore and evaluate cutting-edge agentic AI frameworks (e.g., LangChain, LlamaIndex, AutoGen) for advanced use cases. Data Engineering & Analytics • Construct scalable data pipelines using Databricks (Delta Lake, MLflow, Apache Spark) for large, diverse insurance datasets. • Perform efficient data preparation, feature engineering, and transformation using Python and SQL (Snowflake/Databricks SQL). • Collaborate with cross-functional teams to maintain clean feature stores and cataloged assets. • Translate raw insurance data (claims, policy, billing) into machine learning–ready features. • Write robust unit and integration tests to ensure ML pipeline stability and reliability MLOps & Model Productionization • Implement reliable CI/CD pipelines for ML workflows using platforms like GitHub Actions, Azure DevOps, or Databricks Workflows. • Manage the ML lifecycle; automate experiment tracking, versioning, staging, and deployment with MLflow and model registries. • Monitor models in production for drift and performance, implementing automated alerting and retraining as needed.