Top Remote Fintech Data Science Jobs in New York City, NY

Lead product-focused data science for Cash App Lending: define measurement frameworks, run experiments, analyze customer and risk data, use AI tools to accelerate analysis, partner with product/engineering/risk, drive technical standards, and mentor junior data scientists to inform product and policy decisions.

Lead end-to-end data science for lending products: define measurement frameworks, analyze customer and risk data, design experiments, monitor model and policy performance, and build reusable tooling. Use AI tools and agent workflows to accelerate analysis, mentor junior scientists, set technical standards, and partner with product, engineering, and risk to drive product and business decisions.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Build and productionize traditional machine learning models, owning feature engineering, validation, deployment, monitoring, drift detection, and retraining. Develop LLM-powered agentic tools, dashboards, self-serve analytics products, and automated insight pipelines. Partner with engineering and business stakeholders, write production-grade Python and SQL, drive adoption, improve data quality, and establish responsible AI workflows for a regulated industry.

Develops and validates machine learning and statistical models for anti-money laundering, transaction monitoring, customer screening, and risk rating. The role evaluates AML data quality, integrates vendor solutions, maintains governance and regulatory documentation, leads model lifecycle quality control, and reports performance through management dashboards. It also supports AML risk assessments, audits, regulatory examinations, and cross-functional stakeholder coordination.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

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.

Own Alpaca’s growth data strategy across acquisition, activation, retention, referral, and monetization. Build experimentation frameworks, causal and incrementality analyses, funnel and cohort models, LTV/CAC and churn forecasts, marketing measurement, governed growth metrics, and self-serve analytics. Partner with Product, Marketing, Sales, Engineering, and Finance to influence strategy and roadmaps, communicate insights to leadership, mentor data professionals, and establish standards for growth analytics.