Top Tech Jobs & Startup Jobs in Austin, TX

Lead loss mitigation, build predictive collections models and CECL loss forecasts, design automated conversational recovery strategies, manage credit loss budgeting and vendor selection, and present findings to executive leadership.

Lead fraud detection and mitigation for a conversational Send Now Pay Later product: define first-party fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, integrate ML and decisioning tools (Taktile), and coordinate SARs and compliance reporting.

Lead fraud detection and mitigation for a conversational BNPL product: define fraud typologies, analyze repayment/chargeback trends, own fraud KPIs, design policies, collaborate on ML models and decisioning workflows, and coordinate SARs with Compliance.

Design and own loss mitigation and loss-forecasting frameworks (CECL), build predictive collections models and automated contact strategies (WhatsApp/SMS/omnichannel), align with Operations for recovery execution, manage credit loss budgeting and capacity planning, and lead vendor evaluation and onboarding to maximize recovery ROI.

Lead loss mitigation, forecasting, and collections strategy for consumer lending. Build predictive collections models and CECL-based loss forecasts, align conversational operations, manage credit loss budgeting and vendor procurement, and present results to executive stakeholders.

Lead credit analytics for the Send Now Pay Later product: build and optimize valuation, vintage and NPV models; manage credit policies, portfolio monitoring, and NPL reporting; integrate and test scoring models with engineering/data science; and research alternative data to improve predictive performance.

Lead credit analytics for the Send Now Pay Later product: deliver executive portfolio health reporting, NPL trend analysis, and financial/vintage/NPV modeling. Design end-to-end credit frameworks and acquisition/customer management policies, monitor cohort performance, integrate and test ML scorecards with engineering, and evaluate alternative data sources to optimize approval rates and limit defaults.

Lead fraud risk for a conversational lending product (SNPL): define first-party fraud typologies, analyze repayment and chargeback trends, own fraud KPIs, design automated/manual blocking policies, coordinate ML/rules with central Fraud and Data teams, and liaise with Compliance on SARs and loan abuse.

Lead quantitative credit analytics for a Send Now Pay Later (SNPL) product: build and maintain credit policies, pricing and NPV models, vintage analysis, portfolio monitoring, model integration/testing, and alternative data evaluation to optimize approval rates and manage portfolio health.

Lead design and scaling of a unified fraud and risk platform. Own roadmap, fraud metrics, SQL-based analysis, A/B testing, real-time detection models, and cross-functional delivery to balance customer experience and risk mitigation.