Who We Are:
Credibly believes in small and medium-sized businesses and the people who make them grow. We leverage cutting-edge data science, technology, partner relations, and customer support to provide business owners with accelerated access to right-sized capital solutions.
Founded in 2010, Credibly has sustained rapid growth and provided over $1B in financing to SMBs, while maintaining a strong emphasis on risk management and a culture of compliance. From 2014 to 2016, the company made consecutive appearances on the Inc. 500 list of Fastest Growing Private U.S. companies, as well as Crain's Fast 50 in the State of New York in 2015 and 2016.
In 2017 Credibly became the first company in its space to acquire the servicing rights to a competitor's portfolio ($250MM). Credibly was selected for its proven approach to managing risk. In late 2018, the company completed its first asset-backed securitization and followed with an investment grade senior debt offering in 2019. Credibly's headquarters are in Southfield, Michigan, with offices in New York and Arizona.
The incumbent will be responsible for leveraging analytics and data science across the Risk Management lifecycle in order to improve Credibly’s bottom line. The successful candidate will be able to form solid partnerships with Credit Operations, Technology, Finance and Sales & Marketing.Responsibilities
- Leverage analytics and data science to drive optimal decision-making across the customer risk management lifecycle i.e., acquisition, underwriting, operations, portfolio management and collections. Select examples include:
- Monitoring performance and investment return across acquisition channels and using analytics to improve overall results
- Enhancing underwriting rules, default model and offer logic
- Exploring new data sources to improve overall risk management
- Enhancing early warning portfolio management strategies for accounts that require immediate attention
- Provisioning, liquidity and stress-testing
- Analytics associated with a securitization
- Enhancing collections strategy and collectability model
- Monitoring standard risk management KPIs and taking appropriate actions
- Background of at least 3 years in lending to US consumers or small businesses (small business lending a plus but not required)
- Strong knowledge of US consumer credit bureaus and the craft of lending
- Solid applied statistics and machine learning skills e.g., regression, decision trees, ensemble and boosting techniques
- Expert coding skills including SQL and at least one statistical language such as Python or SAS
- Excellent verbal, written, and interpersonal communication skills
- Ability to thrive in a fast-paced start-up environment
- Creativity and ability to turn data into actionable strategies that will drive business results
- Master’s Degree in a quantitative discipline from a top university