AI practice lead Financial services and Insurance

We are seeking an AI leader to drive innovation and delivery across our Financial Services and Insurance portfolio. Youll oversee the full lifecycle of AI solutions from ideation to production shaping strategy leading multidisciplinary teams and building new capabilities in a fast-evolving market.

EPAM is where tech talent thrivesbuilding groundbreaking solutions advancing your skills through world-class learning platforms and working alongside a global community of problem-solvers to make the future real.

Req#

• Work with clients and internal teams to shape the AI machine learning and agentic business and technology vision and go-to-market offerings
• Manage end-to-end data science artificial intelligence and agentic projects and programs
• Lead multidisciplinary workshops and design sessions with customers
• Develop high-quality proposals in collaboration with subject matter experts and consultants
• Contribute to the evolution of data science artificial intelligence and agentic offerings
• Grow team capacity and capability build new competencies mentor team members and champion transformation with stakeholders

• 10 years of experience as a data science lead machine learning engineering lead or similar roles in banking investment underwriting actuarial or consulting for financial services insurance or reinsurance
• 5 years in a leadership role with team management responsibilities
• Strong communication skills with the ability to explain complex concepts to diverse audiences
• Hands-on experience in at least one domain: computer vision natural language processing recommender systems or time series analytics
• Machine learning engineering and production delivery experience including ML/LLMOps and cloud platforms
• Knowledge of technologies such as Databricks Snowflake or agentic orchestration tools (LangChain Omnigent Semantic Kernel)
• Working knowledge of at least one programming language ideally Python
• Understanding of data science engineering excellence and the modern software development lifecycle for artificial intelligence products
• Consulting experience in a professional services environment

• Current AI leadership experience in a financial services or insurance organization
• Referenceable work such as papers open-source contributions or conference talks in the AI or machine learning space
• Current cloud certifications for Amazon Web Services Google Cloud Platform Microsoft Azure or Databricks
• Experience with regulatory processes and standards such as KYC/AML ISO/IEC FSB IFRS or FINTRAC