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Get to Know UsKafene is revolutionizing the lease-to-own space. We're the point-of-sale powerhouse making flexible lease-to-own accessible to everyone—prime and non-prime customers alike. Our secret weapon? Cutting-edge AI and machine learning that analyzes 20,000+ data inputs in real-time, empowering retailers across furniture, appliances, electronics, tires, and durable goods to say "yes" to more customers.The numbers tell our story: over $500 million in sales and counting. But we're just getting started.Our 150-person team spans NYC headquarters, Wilmington, and remote talent across the globe—all united by a culture that thrives on collaboration, innovation, and genuine support.About the TeamKafene’s Risk team is a key driver of growth for the business. As a Risk Manager, you will report to the VP of Risk and help build Kafene’s profit-driven consumer underwriting strategies. You will harness complex data sources and machine learning, and you will partner across technology and senior leadership to develop strategies that optimize credit risk, fraud risk, and other factors across underwriting, portfolio management, and collections.What You’ll DoLeverage multiple and complex data sources such as Bureau information, alternative data, consumer behavior, the macro environment, and portfolio performance metrics to perform quantitative analyses, classification/decision-tree analyses and/or machine learning modeling to understand root causes and/or potential business opportunitiesTranslate data into meaningful insights, and design, implement and iterate on strategies to drive profitable business growth. Review findings with senior management, like CRO and CEO.Design and manage A/B tests, pilot programs, and controlled experiments to evaluate new strategies, including defining test populations, randomization logic, and success criteria.Build and maintain dashboards and reporting infrastructure to enable real-time monitoring of strategy performance across key metrics.Monitor our acquisition and portfolio performance related to consumer or merchant credit risk, fraud risk, lease amount, term, channel, and other important metrics across the account lifecycle.Monitor both internal and macroeconomic performance to define risk appetite and ensure healthy businesses under different environments.Partner with technology, product, and cross-functional teams to ensure timely and quality implementation with diligent test validation. Track the performance to ensure that it meets expectations.What You’ll BringMaster’s degree in a quantitative discipline such as Statistics, Operations Research, Economics, Engineering, Data Science, or other STEM majors.Minimum 2 years in the financial industry in an analytical function. Experience in credit risk strategy/collection areas is a plusHigh Proficiency in business reporting and analytical tools such as Power BI and, Tableau is requiredHigh-level proficiency in Python, SQL, SAS or other data mining and analytical tools. Familiarity with any decision tree analysis tool, like Enterprise Miner, is a plusExperience of extracting business insights from data analysis and assembling them into clear business insights or recommendations in the financial service/consumer lending industryCompensation and Benefits:Base Salary: Earn a competitive base salary $95,000-$130,000Healthcare: We prioritize your well-being by covering 80% of medical, dental, and vision insurance costs, including coverage for your spouse, children, and other dependents.Retirement Benefits: Begin planning for your future from day one with our 401k plan.Paid Time Off: We understand the importance of work-life balance. That's why we offer flexible paid time off days starting from day one of your employment.We're building a team as diverse as the customers we serve. Kafene is proud to be an equal-opportunity employer, and we mean it.Need accommodation during the application process? We've got you. If you're applying for a U.S. position and require reasonable accommodation at any stage, reach out to careers@kafene.com with details about your request and contact information.
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