Senior Staff Decision Scientist (Multiple Positions) (9673708)

EMPLOYER:  Flexible Finance, Inc.

TITLE:  Senior Staff Decision Scientist (Multiple Positions) (9673708)

LOCATION:  New York, NY - Remote work permitted from any location in the U.S.

DUTIES: 

Shape the design of new credit products, while developing their risk policies and launch strategies to ensure successful market entry. Collaborate cross-functionally with diverse teams to maximize customer lifetime value (LTV), manage financial risk, and drive sustained business growth. Analyze large, complex datasets to solve a wide range of business challenges using advanced analytical and statistical techniques. Develop and implement forecasting models to predict key performance metrics and assess their actual performance. Apply quantitative analysis, data mining, experimentation, and forecasting to support data-driven decision-making and strategic direction. Partner with Product, Engineering, Finance, Operations, and Data Science teams to deliver actionable insights. Build sophisticated reporting and analytics tools that will enable real-time, data-driven decision-making for key stakeholders. Design and develop metrics and dimensions to track and evaluate product and business performance. Present findings and recommendations to stakeholders, including senior leadership, in clear and concise formats.


REQTS:

Must have a Bachelor’s degree or foreign equivalent in Statistics, Economics, Risk Management, Mathematics, or a related field plus six (6) years of experience with credit risk analytics in the position offered, as a Data Science Analyst, Data Science Manager, or a related position. Must have six (6) years of experience with all of the following: Developing data mining and analytics workflows using Python and SQL; Performing portfolio vintage forecasting, CCAR modeling, roll rate forecasting, and delinquency forecasting; Conducting sensitivity analyses and scenario modeling to evaluate financial impact of credit strategy changes and stress conditions; Extracting, transforming, and analyzing large-scale financial data using relational databases including Snowflake and MySQL; Designing and implementing segmentation strategies through decision tree models, clustering algorithms, and logistic regression for credit risk stratification; Designing
and executing controlled experiments (A/B testing and champion-challenger frameworks) to evaluate product and policy effectiveness; and Creating and maintaining dashboards and interactive reports with data visualization tools including Tableau, Sigma, and Google Data Studio to monitor credit performance.

HOURS: Full Time;  Mon-Fri (40 hrs/week)

WAGE RANGE:  $215,000 - $240,000 per year