Back
Tier-1 brand, metro location, and high-demand ML/AI leadership skills create strong competition.
Strongly finance-focused wealth operations and governance requirements increase need for domain-specific backgrounds.
Explicit 10–14 years, people-management, and mandatory production-grade GenAI experience raise filter strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead and manage a team of 15-30 analytics and AI professionals focused on Wealth Operations, delivering advanced analytics and AI solutions including Generative AI and Agentic AI use cases.
Partner with Wealth Operations and related stakeholders to translate complex operational challenges into analytics and AI initiatives that deliver measurable business impact such as cost savings and risk reduction.
Own end-to-end lifecycle of AI/analytics projects including problem framing, solution design, execution, deployment, and adoption across global Wealth Operations workflows.
10–14 years of experience in Analytics, Data Science, or AI, with 3–6 years in people management.
Proven experience delivering production-grade Generative AI and/or Agentic AI solutions with measurable business impact.
Bachelor’s degree in a quantitative field (e.g., Engineering, Mathematics, Statistics, Economics, Computer Science); Master’s degree (MBA/MS) preferred.
Experience working within enterprise constraints like data privacy, latency, and AI model governance; Financial Services or Wealth Operations analytics experience preferred.
Experienced leader skilled at partnering across business, risk, product, and technology teams to translate operational problems into AI-enabled analytics solutions in Wealth Management contexts.
Strong expertise in Generative AI methods (LLMs, prompt engineering) and Agentic AI (workflow automation, orchestration frameworks) combined with deployment experience in complex enterprise environments.
Demonstrated ability to scale AI adoption, build team capabilities in advanced analytics and AI, and deliver measurable business outcomes in global, matrixed organizations.