Job Description

Chubb is a global leader in the insurance industry, committed to delivering innovative solutions that meet the evolving needs of our clients. We are seeking a highly skilled and experienced

Senior Data Scientist

to join our team and play a pivotal role in driving data-driven decision-making and innovation. If you are passionate about leveraging data science, machine learning, and AI to solve complex business challenges, we want to hear from you.


As a Senior Data Scientist at Chubb, you will serve as a subject matter expert in

Predictive Modeling

,

Machine Learning Algorithms

, and

AI Solutions

, with a strong focus on the insurance sector. You will collaborate with business stakeholders to design, develop, and deploy impactful data science solutions that drive measurable value. This role requires a blend of technical expertise, strategic thinking, and exceptional communication skills to ensure the successful adoption of data-driven initiatives across the organization.

Key Responsibilities:

Model Development:

Lead the design and development of machine learning models, ensuring optimal performance and practical application in production environments.

Solution Deployment:

Deploy robust, scalable, and production-ready ML/AI solutions aligned with business objectives.

Collaboration:

Partner with ML Engineers to create scalable systems and model architectures for real-time ML/AI services.

AI Innovation:

Work closely with AI engineers to design and implement AI solutions that address complex business challenges.

Stakeholder Communication:

Translate complex data science and AI concepts into clear, actionable insights for both technical and non-technical audiences.

Quality Assurance:

Review team deliverables, including code and presentations, to ensure high-quality outputs before sharing with stakeholders.

Mentorship:

Mentor and guide team members to foster a high-performance, collaborative work environment.

Project Management:

Plan and manage projects proactively, ensuring seamless product integration and adherence to industry best practices in ML.

Business Impact:

Collaborate with business stakeholders, product owners, and data teams to develop impactful solutions to business problems.

Performance Metrics:

Define and track key performance indicators (KPIs) to measure the value delivered to end-users.

Experience:

Minimum of 6 years of hands-on experience in data science, with a proven track record of deploying ML/AI solutions in production environments. Extensive experience in the insurance sector, with a deep understanding of industry-specific data challenges. Bachelor's or Master's degree in Statistics, Mathematics, Analytics, Computer Science, or a related field. Strong expertise in machine learning techniques, including ensemble methods, decision trees, and regression analysis. Solid understanding of AI fundamentals, including Retrieval-Augmented Generation (RAG) and Agentic frameworks. Advanced proficiency in Python and its data science libraries (e.g., pandas, scikit-learn, TensorFlow). Exceptional presentation and communication skills, with the ability to convey complex findings to diverse audiences. Proven experience working directly with business stakeholders to deliver impactful solutions.

Education:

Bachelor's or Master's degree in Statistics, Mathematics, Analytics, Computer Science, or a related field.

Technical Expertise:

Strong expertise in machine learning techniques, including ensemble methods, decision trees, and regression analysis. Solid understanding of AI fundamentals, including Retrieval-Augmented Generation (RAG) and Agentic frameworks. Advanced proficiency in Python and its data science libraries (e.g., pandas, scikit-learn, TensorFlow).

Soft Skills:

Exceptional presentation and communication skills, with the ability to convey complex findings to diverse audiences. * Proven experience working directly with business stakeholders to deliver impactful solutions.