Senior Data Scientist

Location: Vasanthanagar

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:
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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:
Job Title :
Senior Data Scientist I
Function/Department :
Advance Analytics
Location :
Bangalore, India

Employment Type:

Full-time

Key Responsibilities:

Work with business partners globally to define the scope and requirements of the project, manage deliverables against timelines, implement models and solutions and present of results.
Use broad spectrum of NLP, Machine Learning, including supervised and unsupervised learning, deep learning and GenAI techniques to extract impactful features from unstructured data. Perform data validation, preprocessing, and exploratory data analyses.
Develop and implement models that help with automating the business processes such as Risk Identification, Claims, Research;
Ensure that the model can meet the desired KPIs postproduction.
Build explainable pipelines using descriptive and inferential statistics. Develop adaptable modelling frameworks and reusable assets that can be applied across various projects.
Be a thought leader and generate ideas / novel approaches to solve complex business problems.
Stay abreast of the developments in the rapidly changing field of AI and machine learning.
Handle stakeholder requests and perform work with little to no assistance. Ability to handle multiple projects with dynamic priorities.
Effectively communicate with key stakeholders (both technical and non-technical) in written, oral and presentation formats.
Mentor and coach junior team members and provide support on projects requiring advanced skill and domain expertise.
Gain deeper understanding of Chubb’s business and develop expertise on multiple lines of business.
Skills and

Qualifications:

Strong foundation in machine learning, statistics, and data science, including supervised/unsupervised learning, deep learning, transformer models, GenAI, model tuning and evaluation, with a minimum 3 years of hands-on experience.
Hands-on experience in Python, SQL and working with Relational and NOSQL Databases; familiarity with data engineering, data transformation, analysis, and visualization.
Good experience building NLP, GenAI, LLM, and Agentic AI solutions; knowledge of prompt engineering techniques and evaluation strategies is preferred.
Proficiency with Databricks, cloud platforms, and modern ML/AI development workflows. Knowledge/ Experience in Big data technologies will be an advantage.

Experience with ML libraries and frameworks such as scikit-learn, MLlib, and related tools.
Ability to work with unstructured data, perform data validation/preprocessing, and develop scalable, reusable model pipelines.
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