Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Design, build, and scale production-grade, stateful AI agents integrated into payments, fraud, and product systems. Implement LLMOps observability, containerized deployments, evals-as-code, performance/cost optimizations for RAG pipelines, and mentor engineers to productionize robust agentic workflows.

Lead the fraud data science team to design, build, deploy, and monitor real-time fraud detection models. Perform feature engineering, unsupervised analysis, A/B testing, stakeholder collaboration, and dashboarding to reduce fraud losses and improve model performance and explainability.

As the Identity Product Manager, you will oversee the strategy and development of the identity platform, focusing on customer identification, authentication, and account management. You will collaborate with cross-functional teams to ensure platform extensibility, data integrity, and security while driving significant business impact.

Lead loss mitigation, predictive collections, and loss forecasting (CECL) for consumer lending. Build data models and contact strategies, align conversational operations, manage credit loss budgets, vendor selection, and present risk insights to executive stakeholders.

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.