Lead Data Scientist

• Description and Requirements The Team You Will Join At MetLife, data isn’t just a tool - it is a catalyst for growth. As part of our Data & Analytics organization, you’ll unlock trusted insights that drive bold decisions, power personalized customer experiences, and deliver lasting business impact. Your skills in AI, predictive modeling, and advanced analytics will help solve complex challenges, scale solutions globally, and fuel innovation across every region. We’re building the future of data - one that’s governed responsibly, engineered for scalability, and designed for growth. When you join us, you’re not just supporting the business - you’re empowering it. Let’s transform insight into impact and data into action, together. Key Responsibilities
• Drive data science initiatives supporting enterprise functions (Finance, Actuarial, Legal, Risk, Investment, Strategy) (12%).
• Lead and manage multiple data science initiatives in parallel (15%).
• Partner with business leaders to identify opportunities for AI-driven strategic outcomes (10%).
• Mentor and guide data scientists and junior team members (8%).
• Lead design of analytical solutions and problem identification across business areas (7%). Expand data science use cases and build connections with business stakeholders (6%).
• Develop and deploy advanced analytics and ML models (8%).
• Translate business requirements into analytical frameworks (data prep, modeling, validation) (7%).
• Collaborate with cross-functional stakeholders to deliver models (8%).
• Communicate findings and recommendations to senior leadership (6%).
• Ensure model governance, MLOps, ethical AI, and compliance (8%).
• Collaborate with data engineering/IT for scalable model deployment (5%). 10% domestic travel required.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Telecommunication Engineering, or a related field (will accept foreign education equivalent) and seven (7) years of experience in AI/ML engineering, data science, or related roles. Position requires 3 years of experience performing Data and Analytics functions in financial services or insurance industries.
• Experience implementing Machine Learning models using frameworks and libraries.
• Experience designing, developing, and deploying Generative AI (GenAI) solutions using large language models (LLMs), diffusion models, and GAN models.
• Experience software engineering using Python.
• Experience implementing GenAI solutions using frameworks and libraries.
• Experience implementing best practices for responsible AI, including data privacy, bias mitigation, and model monitoring. Location Expectation This is a hybrid role requiring a minimum of 3 days per week in office. The expected salary range for this position is $138,500.00 to $175,600.00 . This role may also be eligible for annual short-term incentive compensation and stock-based long-term incentives. All incentives and benefits are subject to the applicable plan terms. #LI-DNI