Top Tech Jobs & Startup Jobs in NYC, NY

Develop and deploy machine learning models for fraud detection and credit risk decisioning. Own the full ML lifecycle, including data exploration, feature engineering, experimentation, validation, deployment, monitoring, and optimization. Analyze fraud trends and portfolio outcomes, collaborate with Product, Engineering, and Risk Operations, apply generative AI tools, and mentor fellow scientists while delivering measurable improvements in fraud prevention and responsible credit access.

Own the strategy and roadmap for Dave’s financial data platform, including vendor integrations, data ingestion, normalization, storage, access, quality, and monitoring. Partner with Engineering and Data Science to create financial signals that improve underwriting and repayment prediction. Manage data partners, evaluate new sources, define platform KPIs, and connect data improvements to approval rates, losses, retention, and future credit products.

Own Dave’s organic search and AI discovery strategy, including onsite content, offsite authority, answer-engine visibility, reporting, experimentation, and compliance. Build topical authority, guide writers and agencies, improve citations across AI platforms, and connect organic performance to app installs, member acquisition, and cost efficiency. Partner with product, martech, analytics, brand, partnerships, and compliance teams while shaping the company’s emerging AEO strategy.

Lead large-scale, cross-functional technical programs across product, engineering, operations, data, risk, and compliance. Define roadmaps, coordinate multiple squads and partners, drive system migrations and automation, manage vendors and financial partners, strengthen Agile and CI/CD practices, and communicate program health to senior leadership. Mentor TPMs and improve delivery discipline to increase scalability, reliability, and speed of member-facing financial products.

Lead paid media and user acquisition strategy for new financial product launches. Own channel evaluation, campaign testing, budget allocation, growth forecasting, creative testing, optimization, scaling, and martech readiness. Partner with Product, Finance, Analytics, Marketing, Engineering, and Martech teams to build profitable acquisition engines, establish tracking and dashboards, and improve CAC, LTV, ROI, and unit economics across multiple products.