Top Tech Jobs & Startup Jobs in NYC, NY

Lead design and execution of loss mitigation, predictive collections, and CECL loss forecasting. Build data models and contact strategies, align conversational operations, manage credit loss budgeting, and evaluate third-party vendors to maximize recoveries and protect the balance sheet.

Design and own loss mitigation, predictive collections, and CECL loss forecasting. Partner with Operations to implement conversational contact strategies (WhatsApp/SMS), build propensity-to-pay and recovery models, manage credit loss budgeting and capacity planning, and evaluate/onboard third-party collections vendors and software to protect capital and optimize recoveries.

Lead loss mitigation, forecasting, and collections strategy for consumer lending. Build CECL-based loss forecasts, predictive propensity-to-pay models, automated contact strategies (WhatsApp/omnichannel), manage credit loss budgets, and evaluate third-party recovery vendors while presenting impacts to executive leadership.

Lead credit analytics for the Send Now Pay Later product: build and own valuation and vintage models, manage credit policies, monitor portfolio health and NPL trends, integrate ML scorecards, and evaluate alternative data to optimize approvals and loss performance.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, valuation and NPV models, vintage analysis, executive reporting, model integration and testing, and alternative data integration to optimize approval rates and portfolio health.

Lead credit analytics for the Send Now Pay Later product: own portfolio health reporting, NPL trends, valuation and NPV models, vintage analysis, credit policy design, monitoring, model integration and testing, and alternative data exploration to optimize approval rates and loss performance.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, valuation and NPV models, vintage analysis, portfolio surveillance, executive reporting, model integration/testing, and alternative data exploration to optimize approval rates and manage portfolio risk.

Own strategy for a reusable lending platform and identity data platform. Define identity and authentication flows, data schemas, and API design. Align engineering, fraud, compliance, and partner banks. Drive KPIs, AI-enabled identity decisioning, and platform adoption. Start as a strategist and build a team to scale lending products.

Lead the fraud data science function: define ML strategy, build and deploy real-time fraud detection models, investigate fraud patterns (including lending fraud), run experiments, collaborate with stakeholders, and maintain monitoring and dashboards to minimize fraud losses.

Lead Fraud Data Scientist to define ML strategy, build and productionize fraud detection models (supervised and unsupervised), investigate emerging fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and maintain dashboards tracking fraud KPIs.