Conduct analysis and deliver analytical insights to enable and optimize the end-to-end collection and recovery strategies by using data, machine learning models and advanced analytics tools.
Analyze portfolio performance at a granular segment level on an ongoing basis. Identify trends and conduct root-cause analysis to isolate key performance drivers.
Communicate findings and recommendations to key stakeholders within Collections and Recoveries as well as across the broader Prosper community.
Bring innovative/out of the box thinking to make recommendations and to approach and solve problems.
Design A/B tests and understand the risk-return trade-offs.
Partner with Operations, Risk, Product, Marketing and Engineering teams to implement strategies and monitor strategy performance.
Continue to innovate by testing new data, analytics approaches and models.
Conduct ad-hoc analysis related to risk management, investor services, product, and operations.
Requirements
Bachelor’s degree in business, Statistics, Mathematics, Computer Science, Engineering or Economics and 5+ years relevant experience OR Master’s degree in above areas with 3+ years relevant experience.
Experience in collections, marketing or credit risk management in consumer lending industry is a plus.
Strong analytical and problem-solving skills.
Experience using machine learning and statistical models to develop strategies.
Must have strong proficiency in SQL. Knowledge of R, Python, Tableau, Looker and Knowledge Seeker will be a plus.
Knowledge and experience of segmentation, statistical procedures, and financial analytic tools are required.
Curious to ask questions, probe into reasons and challenge the status quo.
Self-starter and comfortable dealing with ambiguity.
Strong ownership and motivation to drive business results.
Ability to work in a fast-paced environment and meet deadlines without sacrificing quality.