Top Fintech Data Science Jobs in New York City, NY

As a Principal Associate in Data Science, you'll leverage technologies to build knowledge graphs, develop modeling algorithms, and collaborate with cross-functional teams to combat fraud in customer banking.

The role involves analyzing complex data related to private markets, developing data models, creating visualizations, and collaborating on data-driven products.

The Data Scientist will design, build, and deploy machine learning solutions for automating claims adjudication in pet insurance, collaborating across teams, ensuring production readiness and ongoing optimization.

The Senior Data Scientist will leverage data insights to drive growth in lending, foster AI integration, and mentor colleagues while ensuring high-quality data reporting and visualization.

The Senior Associate - Data Scientist will develop AI and machine learning solutions, focusing on model lifecycle management and delivering AI initiatives in collaboration with business teams.

As a Principal Data Scientist at Gusto, you will lead data-driven strategies in payments, collaborate with engineering teams, drive A/B testing, develop predictive models, and build AI-native data products, ensuring data integrity and influencing business decisions.

As a Senior Data Scientist, you will develop predictive models, conduct EDA, collaborate cross-functionally, and drive data-driven decisions.

As a Senior Data Scientist in Fraud Risk, you'll develop metrics, real-time monitoring systems, and implement predictive machine learning models to mitigate fraud while balancing customer experience.

The Senior Director, Global Fraud Analytics will define the global fraud analytics strategy, overseeing product direction and lifecycle management while leading AI initiatives and collaborating with data teams to deliver scalable analytics solutions.

The Director of Data Science leads data science and machine learning initiatives for the Commerce Media platform, aligning strategies with business objectives, overseeing model development, and ensuring best practices in data science processes.