Data & Analytics Engineering – Lead Data Scientist
Job Summary:
This role will provide advanced analytics support within the Business Analytics function that applies the power of data with machine learning to improve business outcomes across the Financial Services business. This team is expected to work closely with the other teams across the organization, including functional teams and the analytic agile squads supporting AI use cases within various business domains. Responsibilities include helping to develop and monitor predictive model and AI solutions to support our pricing, underwriting and clinical review processes, as assigned. Additional responsibilities may include applying machine learning techniques to streamline and automate aspects of these processes, and promoting a culture of data-driven, risk-based decisions.
High Level Job Responsibilities:
- Apply data science techniques to solve business problems across a broad range of data analysis functions including predictive analysis, data modeling, visualization, and data profiling.
- Utilize multiple sources of data, including structured and unstructured data, along with broad range of machine learning techniques to improve insights of the models.
- Support the development of new modeling techniques and procedures.
- Develop and maintain high-quality, robust predictive models and AI solutions using advanced analytic techniques
- Extract and analyze internal and external data sources to help answer key business problems related to risk assessment.
- Interpret data and ML models outputs and provide clear actionable insights and recommendations.
Key Skills:
- Strong knowledge of statistical and data science techniques, including machine learning, data visualization, A/B testing, and experience with databases
- Proficiency in a broad range of data science programming languages, applications and data environments (e.g., Python, R, SQL)
- Experience with machine learning framework and libraries
- Commitment to data compliance, model governance and security protocols
- Strong business acumen to understand why and how the work we do will impact our business stakeholders
- Strong problem-solving skills and effective communication, with an ability to explain technical concepts to a non-technical audience
- BS/MS/PhD in a statistical, mathematical, or technical field (e.g., computer science, actuarial science)
- 5+ years of experience in developing and implementing data science techniques
What will be nice to have?
- Financial services or Insurance experience preferred.
- Demonstrated academic or industry experience with generative AI including prompt engineering, RAG workflows and integrating LLMs into business process.
- Familiarity with ML-Ops practices, including model deployment, monitoring, and life cycle management.
