Senior Data Scientist

Chubb Insurance Hong Kong; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading global insurance provider is seeking a highly skilled Senior Data Scientist to drive data-driven decision-making and innovation. This role requires a minimum of 6 years of experience in data science, with expertise in machine learning and AI solutions. Candidates should be proficient in Python and able to communicate complex findings to diverse audiences. The position offers opportunities for mentorship and collaboration in a high-performance environment.

Qualifications

• Minimum of 6 years of hands-on experience in data science.
• Proven track record of deploying ML/AI solutions in production environments.
• Extensive experience in the insurance sector.

Responsibilities

• Lead the design and development of machine learning models.
• Deploy robust, scalable, and production-ready ML/AI solutions.
• Partner with ML Engineers to create scalable systems.

Skills

Machine Learning

Data Science

AI Solutions

Predictive Modeling

Python

Communication Skills

Project Management

Education

Bachelor’s or Master’s degree in Statistics, Mathematics, Analytics, Computer Science

Tools

pandas

scikit-learn

TensorFlow

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 experiencedSenior Data Scientistto 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 inPredictive Modeling,Machine Learning Algorithms, andAI 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.

Qualifications

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.