Data Analytics Principal/Director - Financial Services

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Data Analytics Principal/Director - Financial Services

Remote in United States of America: Branford, & 2 others

Data Technology Consulting

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We are seeking an exceptional Data Analytics Principal/Director to serve as a trusted partner to senior client executives in Financial Services organizations. This role combines deep data and AI technology knowledge, strong consulting acumen, and proven financial domain experience. You will lead our Financial Services Offering portfolio in Canada, promoting and selling EPAM data expertise in the region. If you can guide senior executives through complex data and AI transformational initiatives, this role is ideal for you.

Req# 1093775223

Responsibilities

• Partner with C-level executives on strategic Data and AI initiatives, including data strategy, enterprise-wide platform enablement, and AI transformations

• Own RFP/RFQ/RFI responses and lead strategic pursuits, including winning strategy development and client storytelling

• Manage the Financial Services project portfolio and build long-term client relationships centered on value delivery

• Lead initial phases of strategic engagements: establish program vision, define success criteria, form teams, and establish governance

• Coach and mentor next-generation consultants in Financial Services Data and Analytics

Requirements

• 15+ years of progressive experience in data technology and consulting, with prior management roles (Senior Manager/Director) at financial institutions or consulting firms supporting financial services clients

• Proven C-level consulting expertise with ability to function as a trusted advisor; hands-on experience with major cloud providers and prominent data ecosystem tools, with emphasis on Databricks and Azure.

• Demonstrated experience in banking (investment or core banking) with deep understanding of data models, processing systems, regulations, and key banking KPIs; knowledge of Basel 2/3, BCBS 239, AML/AFC compliance frameworks

• Strong grasp of data architecture, governance principles, data catalogs, observability frameworks, and ability to lead technical discussions at enterprise scale

• Degree in Computer Science, Information Technology, Applied Mathematics, or similar quantitative field (highly valued)