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.
Qualifications
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.
