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
• Role Overview – Senior Data Scientist

We are seeking a Senior Data Scientist for the Advanced Analytics team, who will be at the forefront of developing new innovative data driven solutions with cutting edge machine learning algorithms. As a Senior Data Scientist, you will build machine learning models, perform quantitative data analysis to enable organizational decision making and develop solutions to complex business problems and create value for the business. This position offers exposure to a wide variety of analytics tools and technologies as well as unique challenges in problem-solving. Building and deploying predictive models in support of our pricing strategy will be a focus area. The ideal candidate will possess a strong background in statistical modelling, machine learning, and data analysis. In this role, you will collaborate with cross-functional teams to extract insights from complex data sets, develop predictive models, and implement innovative solutions that enhance business performance.

Responsibilities

• Work with business partners globally, manage deliverables against timelines, presentation of results and implement the model.

• Synthesize data to uncover inherent trends, assess impact of data on business usage, and to make recommendations for improvement.

• Build GLM pricing models/machine learning models in support of various property and casualty insurance products.

• Research, recommend, and implement statistical and other mathematical methodologies appropriate for the given business problem.

• Build explanatory and forecasting models using descriptive and inferential statistics, and regression analysis.

• Perform data validation, preprocessing, and exploratory data analyses.

• Communicates analytical goals, approaches, outcomes, and insights to both technical and non-technical audiences.

• Collaborate with business partners and peers within the organization to understand and scope the problem, gather business requirements, and develop robust model solutions that drive improvement in key business metrics.

• Effectively communicate with key stakeholders (both technical and non-technical) in written, oral and presentation formats.

• Create/Maintain excellent working relationships with business partners across the Chubb organization including Product, Actuarial, IT, and analytics peer groups.

• Develop adaptable modelling frameworks and reusable assets that can be applied across various projects.