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Senior data scientist (Insurance analytics)
EY GDS is looking for a motivated, result oriented and quality focused experienced and skilled data scientist who has deep knowledge and expertise in developing insurance analytics solutions. The candidate will be responsible for delivering high-quality analytical solutions to our clients in the insurance industry, using advanced techniques and technologies.
- Lead a team of AI/ML experts to deliver high-quality solutions for clients
- A data scientist having good business understanding, capable of translating business requirement into analytical and OR problem.
- Lead and manage analytics projects for insurance clients from end-to-end, including problem definition, data acquisition, model development, validation, deployment and monitoring
- Work closely with clients and stakeholders to understand their business needs and objectives, and translate them into analytics problems and solutions
- Provide thought leadership and guidance on best practices and methodologies for insurance analytics
- Architect and implement scalable and robust analytics solutions using Python and next generation technologies such as cloud, big data, AI/ML, etc.
- Get involved in business development, client engagement, proposal writing and presentation of the solutions to senior stakeholders and clients.
- Present and communicate the results and insights of the analytics solutions to clients and stakeholders in a clear and effective manner
- Mentor and coach junior analysts and developers on the team
- 6-8 years of experience in analytics, with at least 5 years of experience in insurance analytics
- Strong expertise in the application of analytical and AI techniques, such as optimization, simulation, machine learning, deep learning, natural language processing, computer vision, etc.
- Knowledgeable with the underwriting and claims processes of various insurance products, and familiar with the specific problem areas and analytics models to be developed
- High expertise in Python and next generation technologies such as cloud, big data, AI/ML, etc.
- Proficient in Python and SQL programming
- Strong knowledge of Pandas and Numpy libraries.
- Excellent mathematical, statistical, and analytical skills.
- Understanding of end-to-end product development lifecycle in different environments such as dev, QA, and production.
- Git version control and Agile development experience.
- Experience in architecting and working on end-to-end analytics project lifecycle, including data acquisition, model development, validation, deployment and monitoring
- Ability to manage clients and stakeholders effectively and build strong relationships
- Ability to translate business problem into analytics problem and vice versa
- Excellent presentation and consulting skills
- Manage end to end project delivery- scoping, solutioning, designing, developing, testing, deploying or maintaining.
- Ensuring the solutions meet the client requirements and expectations
- Communicate effectively with the clients and internal stakeholders throughout the project
- Identify new opportunities and generate proposals for potential clients
- Present the solutions and showcase the value proposition to senior stakeholders
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