Title: Senior Quantitative Risk Analyst

Duties: The Senior Quantitative Risk Analysts (Multiple Positions Open) at Chime Financial, Inc. in San Francisco, California will play a key role in developing the customer segments based on risk and value that will drive the risk limits, policies, and strategy for all our current and future products. Specifically, the position will work closely with product, machine learning, and analytics teams and will interact with business stakeholders across many departments. Leverage statistical and financial engineering skills to reduce various risks involved in offering member friendly product features to our digital banking customers. Research new financial products or analytics to determine their usefulness. Build customer risk segments to optimize our risk limits, policies, and strategy for various product features (ATM withdrawal, Spend, ACH, MCD etc.) and provide the best possible customer experience while minimizing financial losses. Analyze customer transaction activity and identify attributes that predict customer’s risk and value (as early in the customer lifecycle as possible). Maintain or upgrade all financial risk models in use as needed. Work closely with the user research team to incorporate behavioral based member insights into the customer risk segmentation strategy. Responsible for partnering with cross functional teams (Finance, Growth, Product, Member Services etc.) to incorporate customer risk segments into their workstreams.

This notice is subject to Chime Financial Inc.'s employee referral program.

Requirements: A Master’s degree in Finance or Financial Engineering plus 2 years of risk modeling and financial engineering experience. The experience must also include each of the following:  (1) Two years of risk analytical and modeling experience in a quantitative risk role at a FinTech company or in the lending industry; (2) Two years of experience analyzing risk data using Python, R, and SQL; (3) Two years of experience with data visualization tools including Tableau or Looker; (4) One year of experience applying regression models, decision tree models, or other machine learning models to segment customers based on their credit or fraud risk; and (5) One year of experience developing risk models, limits, and policies in the Fintech industry.

Interested candidates can email their resume to apply to Diana Yau at [email protected] and reference job code 041.  Contact Diana Yau at [email protected] if you have questions or need information about this application.