Retail Lending & Credit Analytics SME
Location: New Jersey, New York, Pennsylvania (Remote with occasional travel)
About Us:
Our passion at EXL is enabling organizations to achieve a measurable, competitive advantage through Data Management. We partner with our clients to design and implement scalable, accessible, and innovative solutions. Our goal is to make sense of data to drive client’s business forward through data strategy, data governance and building cloud data platforms. EXL is a leading data analytics and digital operations and solutions company that partners with clients to improve business outcomes and unlock growth. By bringing together deep domain expertise with robust data, powerful analytics, cloud, artificial intelligence and machine learning, we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquarters in New York, our team is over 73,000+ strong, with more than 50 offices spanning six continents
Role Summary
We are seeking a seasoned Retail Lending Domain Subject Matter Expert with deep banking and financial services experience across consumer lending products. This person will be the business and domain authority on a bank’s BI and analytics modernization program. The client’s technology team has limited retail lending knowledge, so this role leads the business conversation: defining what should be measured, how each metric is derived, and how reporting should be structured so that it is accepted by the end business users. Delivery is carried out by a technical team, and the SME ensures that what is built is correct, meaningful and aligned to how retail lending actually works.
Roles and Responsibilities
- Act as the retail lending subject matter expert for the program, driving requirements with senior client stakeholders and guiding the client’s IT and data teams on what the business needs.
- Define, derive and document key retail lending metrics (for example delinquency and roll rates, charge-offs, vintage performance, approval and booking rates, utilization, balances, losses and revenue), including business logic, calculation rules, and hierarchies.
- Apply strong knowledge of retail lending products, processes, data and performance drivers to guide the design of reports, KPIs and analytical use cases.
- Own metric governance from the business side: ensure consistent definitions and alignment across Product, Risk, Finance and Technology teams, and resolve discrepancies between teams.
- Review and validate reports and outputs built by the delivery team (onshore and offshore), identify the likely source of any data mismatch, and work with the client’s data provisioning teams to resolve it.
- Perform and guide analytics on portfolio performance, credit quality and customer behavior to ensure that reporting reflects real business insight.
- Partner with senior stakeholders to prioritize use cases by business value, impact and feasibility, and support the transformation roadmap and delivery priorities.
- Translate business needs into clear business requirements, metric specifications and acceptance criteria for the technical team, and support UAT through to production.
- Mentor team members and build stronger banking-domain knowledge across the technical delivery team.
Required Qualifications
- 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, Mortgage and other consumer products, including a strong grasp of the credit lifecycle from acquisition through collections and charge-off.
- Proven experience in analytics around retail lending, such as portfolio performance, delinquency and loss analysis, vintage analysis, credit strategy or line management, and risk monitoring.
- Demonstrated ability to define and derive business metrics and to document metric logic, definitions and hierarchies in a way that technical teams can implement.
- Ability to lead client conversations at a senior level and to guide stakeholders on what they should measure and why.
- Working knowledge of SQL or similar data tools, sufficient to understand the 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.
Preferred Qualifications (Good to Have)
- Experience in a 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 (Databricks, Snowflake, data lakes, lakehouse).
- 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 (for example CECL and CCAR).
- Experience working in a consulting or client-facing delivery model.
Oversee organizational data engineering solutions. Lead highimpact initiatives. Ensure alignment with organizational goals. Provide executive guidance.
Bachelor's or Master's degree in Data Science, Computer Science, or related field. 8-12 years of experience in data engineering or related field.
