MetLife

Job Responsibilities:

• Lead all stages of Data, analytics & AI product development life cycle: from problem identification, conceptualization, prioritization to solution development and delivery.
• Contribute to hands-on development of data & analytics solutions.
• Collaborate with business and technology partners to co-create solutions anchored on customer care, human-centered design, frictionless services, and meaningful engagement.
• Develop Data and Analytics roadmaps. Deliver solutions with transformational impact to the Enterprise.
• Communicate, engage, and present roadmaps, use cases, solutions and impact to senior management.
• Deliver products and solutions in a timely, proactive, and entrepreneurial manner.
• Institutionalize best practices, contribute to research and experimentation efforts.
• Accelerate solution delivery using re-usable frameworks, prototypes and hackathons.
• People leadership: talent acquisition, coaching and mentoring team.

Education and Technical Skills:

• Bachelor’s/Master’s degree in an information technology/computer science or relevant domain. MBA or financial services industry experience preferred;
• 10-14+ years of relevant experience in data and analytics product & solution delivery

• Traditional as well as modern statistical and machine learning techniques
• Azure ML, OpenAI, Python, PyTorch , SQL, and TensorFlow
• Experience working with large and complex internal, external, structured and unstructured datasets.
• Responsible deployment of AI. Developing and maintaining detailed technical documentation.
• Solution Engineering and Consultative skills: Strong conceptual and creative problem-solving skills 
• Agile methodologies & tools. 
• Excellent written, verbal communication skills and presentation skills; engage in meaningful manner with variety of audience: business stakeholders, technology partners & practitioners, executive and senior management. 
• Industry knowledge about emerging AI trends, AI tools and technologies, 
• Familiarity of new age AI and ML techniques such as GenAI, foundational models, large language models (LLMs) and applications
• Certifications in AI space such as ML Ops, AI Ops, Generative AI, Ethical AI, AI in cloud
• Management consulting experience