Assistant Vice President

EXL•New Jersey, NJ

2h•Remote

About The Position

EXL is seeking a seasoned Retail Lending Domain Subject Matter Expert to serve as the business and domain authority for a bank’s BI and analytics modernization program. The role leads business discussions and guides client IT and data teams in defining what should be measured, how metrics are derived, and how reporting should be structured. The SME partners with the technical delivery team to ensure that solutions are accurate, meaningful, and aligned with retail lending practices. The role focuses on consumer and retail lending products, portfolio analytics, metric governance, reporting and KPI design, and collaboration with senior stakeholders across Product, Risk, Finance, and Technology. The position is remote in New Jersey, New York, or Pennsylvania, with occasional travel. The posting also includes a separate responsibilities and qualifications section describing oversight of organizational data engineering solutions, leadership of high-impact initiatives, alignment with organizational goals, executive guidance, and a degree and experience profile in data engineering or a related field.

Requirements

10+ years of experience in banking or financial services, with a strong focus on consumer or retail lending.
Deep, hands-on experience with retail lending products such as credit cards, personal loans, mortgages, and other consumer products, including the credit lifecycle from acquisition through collections and charge-off.
Proven experience in retail lending analytics, such as portfolio performance, delinquency and loss analysis, vintage analysis, credit strategy or line management, and risk monitoring.
Ability to define and derive business metrics and document metric logic, definitions, and hierarchies for technical implementation.
Ability to lead senior-level client conversations and guide stakeholders on what to measure and why.
Working knowledge of SQL or similar data tools to understand data, review outputs, and trace discrepancies.
Strong stakeholder-management skills, including experience with senior business, risk, finance, and technology leaders.
Excellent verbal, written, and executive-level presentation skills.
Bachelor's or Master's degree in Data Science, Computer Science, or a related field.
8–12 years of experience in data engineering or a related field.

Nice To Haves

Experience in BI, reporting, or analytics transformation or modernization within a bank or financial institution.
Hands-on familiarity with Power BI or similar BI tools, including semantic models, dashboards, and role-based access.
Exposure to data engineering, data architecture, dimensional modeling, or modern data platforms such as Databricks, Snowflake, data lakes, or lakehouses.
Experience working with offshore or multidisciplinary delivery teams, including data engineers, modelers, and BI developers.
Familiarity with credit risk, underwriting, collections, finance, and regulatory reporting such as CECL and CCAR.
Experience working in a consulting or client-facing delivery model.

Responsibilities

Act as the retail lending subject matter expert, drive requirements with senior client stakeholders, and guide client IT and data teams on business needs.
Define, derive, and document retail lending metrics, including business logic, calculation rules, and hierarchies.
Use knowledge of retail lending products, processes, data, and performance drivers to guide reports, KPIs, and analytical use cases.
Own business-side metric governance, ensure consistent definitions across Product, Risk, Finance, and Technology, and resolve discrepancies.
Review and validate reports and outputs from onshore and offshore delivery teams, identify likely sources of data mismatches, and work with client data provisioning teams to resolve them.
Perform and guide analytics on portfolio performance, credit quality, and customer behavior.
Partner with senior stakeholders to prioritize use cases by business value, impact, and feasibility, and support transformation roadmaps and delivery priorities.
Translate business needs into business requirements, metric specifications, and acceptance criteria; support UAT through production.
Mentor team members and strengthen banking-domain knowledge across the technical delivery team.
Oversee organizational data engineering solutions, lead high-impact initiatives, ensure alignment with organizational goals, and provide executive guidance.