Manager - Data Science

Responsibilities

• Work closely with a team of data scientists to design, build, and test machine learning models to solve complex business challenges.
• Research and implement state-of-the-art modeling approaches, including zero-shot/few-shot learning, embedding techniques, and fine-tuning.
• Ensure high-quality, secure code that meets business objectives and quality standards.
• Build reusable tools to streamline the modeling pipeline and facilitate knowledge sharing.
• Manage project stakeholder expectations and communicate progress effectively.
• Adapt to shifting priorities while maintaining momentum and meeting deadlines.

Requirements

• 10+ years of experience in Machine Learning (ML) with deep expertise in writing and reviewing production code in Python.
• Experience with LLM tooling and frameworks such as LangChain or LlamaIndex.
• Proven experience designing scalable, end-to-end Machine Learning and NLP systems.
• Strong understanding of NLP techniques including text pre-processing, entity extraction, and encoder-decoder architectures.
• Experience building software using containerization technology like Kubernetes and Docker.
• Familiarity with frameworks such as FastAPI and Uvicorn, and CI/CD tools like Jenkins.
• Knowledge of distributed, high-throughput, and low-latency architectures.

Benefits

• Hybrid work environment and flexible work options.
• Comprehensive health, dental, and vision coverage.
• Savings and investment plans including Corporate NPS and Employee Stock Purchase Plan (ESPP).
• Upskilling opportunities through education reimbursement and certification programs.
• Employee Assistance Program (EAP) and yearly free health campaigns.

About the Company

Chubb is a world leader in insurance, providing commercial and personal property and casualty insurance, reinsurance, and life insurance across 54 countries. At Chubb India, we are undergoing a digital transformation driven by engineering excellence and analytics. We foster a start-up mindset within a global organization, encouraging innovation, collaboration, and continuous learning.