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 (., 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 (., 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.
