Lead Data Scientist

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
• Role Overview – Lead Data Scientist

We are seeking a Lead Data Scientist with 5+ years of experience to lead and deliver impactful data science solutions. The ideal candidate should possess deep expertise in machine learning algorithms(GLM, Neural Networks) which include EDA, feature engineering, and proficiency in coding using Python, SQL, and comfortable on cloud-based platforms like Databricks (must). This role emphasizes strong conceptual understanding, clear interpretation and communication of outcomes, team building, and talent development. Experience with big data platforms, neat documentation, coding best practices, collaborative development using GitHub, and robust model monitoring is essential.

Responsibilities:

• Collaborate with stakeholders to define business problems and translate them into data science projects.
• Gather, clean, and preprocess data from multiple sources using Python and SQL on platforms like Databricks.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and data quality issues.
• Engineer features to enhance model performance and interpretability.
• Select, develop, and validate machine learning models (GLM, GenAI, neural networks).
• Monitor model performance post-implementation, ensuring accuracy, stability, and business relevance over time.
• Maintain clear, organized, and comprehensive documentation for all data science processes, code, and methodologies.
• Use GitHub for version control, code review, and collaborative development.
• Work closely with business partners to gather requirements and ensure alignment on project goals.
• Present complex technical findings in a clear, actionable manner to both technical and non-technical audiences.
• Provide recommendations based on model insights to drive business decisions.
• Foster a collaborative, inclusive, and high-performing team environment.
• Mentor and coach junior data scientists, supporting their technical and professional growth.
• Lead knowledge sharing sessions and promote best practices in data science and analytics.