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- Tasks: Lead the development of machine learning models and deploy AI solutions in the insurance sector.
- Company: Chubb, a global leader in innovative insurance solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact by solving complex business challenges with data science and AI.
- Qualifications: 6+ years in data science, strong ML expertise, and excellent communication skills.
- Other info: Join a collaborative team focused on innovation and high-performance outcomes.
The predicted salary is between 43200 - 72000 £ per year.
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.
- Bachelors or Masters 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.
- Bachelors or Masters 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.
Senior Data Scientist employer: Description Chubb
Contact Detail:
Description Chubb Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or conferences related to data science and insurance. You never know who might have a lead on your dream job!
✨Show Off Your Skills
Create a portfolio showcasing your best projects, especially those involving machine learning and AI solutions. Share it on platforms like GitHub or your personal website to impress potential employers.
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies. Be ready to discuss your past projects and how they’ve made an impact, especially in the insurance sector.
✨Apply Through Us!
Don’t forget to check out our website for openings at Chubb. Applying directly through us can give you an edge, as we’re always looking for passionate candidates who fit our culture!
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Scientist role. Highlight your expertise in machine learning, AI, and any relevant projects you've worked on in the insurance sector.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our team. Be specific about your experience with predictive modelling and your ability to communicate complex ideas clearly.
Showcase Your Projects: Include links or descriptions of past projects where you've deployed ML/AI solutions. This gives us insight into your hands-on experience and problem-solving skills in real-world scenarios.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows your enthusiasm for joining our team!
How to prepare for a job interview at Description Chubb
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning techniques and AI fundamentals. Be ready to discuss specific models you've developed, the challenges you faced, and how you overcame them. Chubb is looking for someone who can demonstrate a deep understanding of predictive modelling and its application in the insurance sector.
✨Showcase Your Collaboration Skills
Prepare examples of how you've worked with cross-functional teams, especially with ML engineers and business stakeholders. Highlight your ability to translate complex data science concepts into actionable insights that non-technical audiences can understand. This will show that you can bridge the gap between technical and business needs.
✨Be Ready to Discuss Impact
Think about the business problems you've solved with your data science solutions. Be prepared to share metrics or KPIs that demonstrate the value your work has delivered. Chubb wants to see how your contributions have made a tangible impact on previous projects.
✨Practice Your Presentation Skills
Since communication is key for this role, practice explaining your past projects and findings clearly and concisely. Use storytelling techniques to make your experiences engaging. This will help you convey your expertise effectively during the interview.
