Job Description

Job Title: Senior Data Scientist

Experience Level: 6-10 years

We are seeking a strong candidate with significant experience in the insurance sector and a strong background in data science to fill an exciting Senior Data Scientist position at Chubb. The Senior Data Scientist is expected to be a subject matter expert in Predictive Modelling and Machine Learning Algorithms and will work closely with business stakeholder to deliver impactful solutions, drive adoption, and articulate value.

Responsibilities

Spearhead the design and development of machine learning models, with a keen eye for practical application and great intuition for its performance in production. Deploy production-ready solutions ensuring robustness, scalability, and alignment with business goals. Collaborate closely with ML Engineers to design scalable systems and model architectures that enable real-time ML/AI services. Articulate intricate data science concepts and findings to a varied audience, ensuring clarity for both technical and non-technical stakeholders. Review the team's deliverables before sharing them with business stakeholders, including codes, presentations. Coach individuals in the team and build a high-performance workplace. Proactive plan and manage projects, anticipate product integration and drive thought leadership in bringing the best ML practices from the industry. Collaborate with the Business stakeholders, product owners and other data teams to build impactful solutions to business problems. Define key performance metrics that accurately reflect the value delivered to end-users.

Desired Qualifications

Minimum 6 years of hands-on experience in data science, with a proven track record in deploying ML models in production environments. A bachelor’s or master’s degree, preferably in Statistics, Mathematics, Analytics or Computer Science.   Experience in the insurance sector with an understanding of industry-specific data challenges. Strong foundation in a variety of machine learning techniques, including but not limited to ensemble methods, decision trees, and regression analysis. Advanced proficiency in Python and its data science libraries (e.g., pandas, sci-kit-learn, TensorFlow). Excellent presentation and communication skills, with the ability to effectively convey complex findings to both technical and non-technical stakeholders. Prior experience in working directly with the business stakeholders.