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Senior Data Scientist

2 months ago

London, Greater London, United Kingdom Chubb Full time

Job Title: Senior Data Scientist

Job Summary:

Chubb is seeking a highly skilled Senior Data Scientist to join our team. As a Senior Data Scientist, you will be responsible for designing and developing machine learning models, deploying production-ready solutions, and collaborating with business stakeholders to deliver impactful solutions.

Key Responsibilities:

  • Model Development: Spearhead the design and development of machine learning models, with a keen eye for practical application and great intuition for its performance in production.
  • Solution Deployment: Deploy production-ready solutions ensuring robustness, scalability, and alignment with business goals.
  • Collaboration: Collaborate closely with ML Engineers to design scalable systems and model architectures that enable real-time ML/AI services.
  • Communication: Articulate intricate data science concepts and findings to a varied audience, ensuring clarity for both technical and non-technical stakeholders.
  • Review and Coaching: 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.
  • Project Management: Proactive plan and manage projects, anticipate product integration and drive thought leadership in bringing the best ML practices from the industry.
  • Collaboration with Business Stakeholders: Collaborate with the Business stakeholders, product owners and other data teams to build impactful solutions to business problems.
  • Performance Metrics: Define key performance metrics that accurately reflect the value delivered to end-users.

Desired Qualifications:

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