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

The Principal Data Scientist will lead analytics strategies, drive execution, mentor junior scientists, and innovate analytical practices for business decisions.

The Senior Product Analyst will support the Consumer Product team with KPI reporting, exploratory analysis, A/B testing, and dashboard creation to drive product growth and performance understanding.

The Staff Analyst will design and analyze pricing experiments, optimize pricing strategies, conduct market trend analyses, and collaborate with cross-functional teams to enhance marketplace outcomes.

Lead the data science team in developing and deploying advanced machine learning models to improve decision-making and efficiency. Collaborate cross-functionally while mentoring staff and managing the data science function.

Manage data analysts and scientists focused on payments products and compliance. Responsible for data analytics, team growth, and cross-functional partnerships.

Lead a data science team focused on customer service excellence, utilizing analytics and machine learning to drive optimization and improve user experiences at Coinbase. The role emphasizes partnership across departments to enhance metrics and frameworks.

As a Senior Data Scientist, you will deliver real-time insights, develop and productionize ML models, design data workflows, and collaborate across teams.

The Data Scientist II estimates, develops, and implements consumer credit models related to mortgage metrics and utilizes statistical methods and machine learning. This role involves cloud computing, data analysis, and communication of findings to nontechnical teams.

The Senior Data Scientist will develop machine learning models, collaborate with cross-functional teams, and help improve credit risk assessments to drive business growth.

As an AI-First Data Scientist, you will design and deploy ML solutions, conduct causal analysis, and automate intelligence in decision-making processes. You will work closely with senior operators and business leaders, translating complex problems into data-driven solutions while ensuring model performance and scalability.