Consultant, Data Science and Analytics (Credit Risk)

Team Overview:

The team is part of TransUnion's Data Science & Analytics organization and supports lenders operating in the U.S. short-term lending market. The team delivers data-driven insights, credit risk strategies, predictive analytics, and customer-focused solutions that help clients improve portfolio performance, optimize lending decisions, and drive business growth.

The team partners closely with Sales, Product, and Analytics functions across TransUnion to develop innovative solutions, enhance customer value, and support revenue growth through analytics-led engagements.

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Role Overview and Core Responsibilities:

• Lead analytic client engagements involving descriptive, predictive, and prescriptive analysis, using techniques such as segmentation, logistic regression, machine learning, and scenario/strategy analysis.
• Deliver analytic insights and recommendations in succinct, compelling presentations for internal and external customers.
• Partner with cross-functional teams to identify growth opportunities, improve risk management practices, and support the development of value-driven analytics solutions for customers.
• Design and write programs for model development, performance monitoring, strategy evaluation, and large-scale data analysis using languages such as R, Python, SQL, Spark, and cloud-based platforms.
• Provide mentorship and training to junior colleagues and manage progress across multiple initiatives under limited direct supervision.
• Foster a high-performance culture and cultivate an environment that promotes excellence and reflects the TransUnion brand.
• Support continuous innovation by evaluating emerging analytical techniques, technologies, and industry trends to enhance business outcomes.

Required Knowledge and Experiences:

• Master's degree in statistics, applied mathematics, financial mathematics, operations research, or another highly quantitative field, with at least five (5) years of professional experience performing advanced analytic work in financial services, consumer credit, or a related industry.
• Working knowledge of consumer lending and credit risk management practices, including familiarity with credit bureau data and business practices.
• Exceptional interpersonal and communication style, with the ability to communicate effectively at multiple levels within and outside the organization.
• Proven experience applying statistical and predictive modeling techniques to support business decision-making and measurable customer outcomes.
• Strong project management skills, with ability to manage competing priorities and deliver results in a fast-paced, collaborative, and matrixed environment.