Risk and Data Science Analyst: Building a whole new type of credit card (Los Angeles) - FinTech (PingLend, YC W21)

Why you should join PingLend

PingLend is on a mission to radically change the way credit works for the underbanked: starting with credit. We just wrapped up a Series A less than one year after our seed round and are in ultra-growth mode.

PingLend allows almost anyone to get a credit card regardless of their credit score by collateralizing assets such as gold, jewelry, watches, handbags, etc. This allows PingLend's users to build their credit and qualify for previously unobtainable financial products. Soon we will expand to every type of collateral, across physical and virtual goods.

The Risk/Data Science role We are looking for an analyst ready to help build a fintech unicorn and change the lives of underbanked Americans. We are working on revolutionizing credit by pioneering our novel approach to asset collateralization. Achieving this objective requires outstanding risk management and data analytics.

Key responsibilities: -Conduct insightful analysis using internal and external data (e.g., revenue, risk, product, market, industry) to derive insights that will drive business decisions -Explore and test new data sources and techniques to improve our decisioning. -Leverage data techniques to investigate our data and gain knowledge of our users/business, and educate the rest of the team -Design and execute acquisition, pricing, credit line tests -Partner with engineers to validate & deploy solutions in an efficient, sustainable & usable manner Characteristics of a successful candidate: -1-3 years of experience in analytical function (e.g., data science, risk management, or strategic finance) or equivalent master’s degree -Self-starter, capable of productive work both independently and as part of the team, with a desire to learn quickly and take ownership -Strong track record in working collaboratively -Ability to multi-task in a fast-paced environment is essential, with prior experience in consumer finance or fintech strongly preferred -Strong knowledge of Excel, SQL, and experience with a programming language (preferred but not required) -Understanding of credit cards and valuation techniques preferred