Develop and apply statistical theories and methods to summarize numerical data to provide usable information to management of consumer lending corporation. Perform statistical and decision-tree analyses of complex data to understand root causes and/or potential business opportunities and optimize credit and leasing decisions. Extract meaningful business insights through the statistical analysis of complex data by organizing, aggregating, and summarizing relevant risk data from multiple and complex data sources (such as credit bureau information, alternative data, consumer behavior, the macro environment, and portfolio performance metrics). Validate and apply credit risk score models/strategies to optimize credit risk, fraud risk, and other risk strategies across the account lifecycle. Develop statistical reports to monitor Kafene's acquisition and portfolio performance related to credit risk, fraud risk, pricing, and other important metrics across the account lifecycle. Transfer data into meaningful, professional, and easy to understand formats giving business insight to leadership using knowledge of risk management framework and regulations. Share observations and present a variety of performance results with senior management, including the Chief Risk Officer (CRO) and Chief Executive Officer (CEO). Propose innovative credit risk strategy recommendations to drive profitable business growth. Review findings with senior management. Monitor internal and external performance to consider different macro economies and define risk appetite to ensure healthy businesses under different environments. Partner with Kafene's technology team and other partners to ensure timely and quality implementation with diligent test validation. Track the performance to ensure that it meets expectations. Design strategies incorporating statistics-based risk modeling analyses and develop time series loss forecast models to evaluate the expected losses of the portfolio and share it with finance and other internal stakeholders to get alignment. Evaluate 3rd party vendors' statistical data like the US Credit Bureau and score products to further improve Kafene's models and strategies. Analyze consumer lending profit and loss (P&L) components and dynamics. Use statistical analysis tools such as Python, SQL, R and SAS.Requires Master's degree in Statistics, Operations Research, Economics, Engineering, Data Science, or related. 5 years of experience in job offered or related occupation such as Statistician, Analytics Associate, Analytics Analyst, Risk Analyst, or related occupation in the consumer banking or lending industry. Experience must have included 5 years: extracting meaningful business insight from statistical analyses of complex data using knowledge of risk management framework and regulations; validating and applyingcredit risk score models to optimize credit risk and other risk strategies; and proposing innovative credit risk strategy recommendations to senior management; 3 years of experience: using statistical analysis tools such as Python and SQL; and analyzing consumer lending profit and loss (P&L) components and dynamics. Able to telecommute with manager approval, but must work onsite at HQ 3-4 times per week.Minimum Salary: 163,240Maximum Salary: 175,000Salary Unit: Yearly#J-18808-Ljbffr
