Lead Data Scientist

Lead Data Scientist at MetLife, focusing on driving data science initiatives for enterprise functions like Finance, Actuarial, Legal, Risk, Investment, and Strategy. The role involves leading multiple data science initiatives, partnering with business leaders to identify AI-driven opportunities, mentoring junior team members, and designing analytical solutions. Key responsibilities include developing and deploying advanced analytics and ML models, translating business requirements into analytical frameworks, and ensuring model governance, MLOps, ethical AI, and compliance. Collaboration with data engineering/IT for scalable model deployment is also crucial. The role requires experience in implementing ML models, Generative AI (GenAI) solutions using LLMs, diffusion models, and GANs, software engineering with Python, and best practices for responsible AI.

What you'd actually do

  1. Drive data science initiatives supporting enterprise functions (Finance, Actuarial, Legal, Risk, Investment, Strategy) (12%).
  2. Lead and manage multiple data science initiatives in parallel (15%).
  3. Partner with business leaders to identify opportunities for AI-driven strategic outcomes (10%).
  4. Mentor and guide data scientists and junior team members (8%).
  5. Lead design of analytical solutions and problem identification across business areas (7%).

Skills

Required

  • Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Telecommunication Engineering, or a related field
  • seven (7) years of experience in AI/ML engineering, data science, or related roles
  • 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

Nice to have

  • Mentor and guide data scientists and junior team members
  • Collaborate with cross-functional stakeholders to deliver models
  • Communicate findings and recommendations to senior leadership
  • Collaborate with data engineering/IT for scalable model deployment

What the JD emphasized

  • 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 implementing GenAI solutions using frameworks and libraries.
  • Experience implementing best practices for responsible AI, including data privacy, bias mitigation, and model monitoring.
  • Ensure model governance, MLOps, ethical AI, and compliance

Other signals

  • Develop and deploy advanced analytics and ML models
  • Ensure model governance, MLOps, ethical AI, and compliance
  • Collaborate with data engineering/IT for scalable model deployment