Vice President, Data Scientist (Open Finance)

Mastercard is building advanced data science and AI capabilities for its Open Finance business, and this role will help define and scale that organization. As a senior leader, you will set the data science strategy, drive production-grade machine learning and generative AI use cases, and translate customer and business needs into scalable solutions. This position is based in New York, NY (onsite).

Compensation: $233,000 - $390,000 per year. Pay range varies by location, including New York City, NY: $244,000 - $390,000 and Purchase, NY: $233,000 - $374,000.

What you’ll do

• Define and execute the Data Science strategy for Open Finance in alignment with business and product objectives.
• Identify where advanced analytics, machine learning, and AI can differentiate products, improve decisioning, reduce risk, and drive growth.
• Build a scalable roadmap from foundational intelligence capabilities to application-specific models and solutions.
• Evaluate and adopt modern advances in machine learning, generative AI, foundation models, LLMs, deep learning, NLP, and other emerging technologies when they create meaningful business value.
• Ensure solutions deliver accuracy, scalability, explainability where required, resiliency, and continuous improvement based on performance and changing market conditions.
• Lead continuous development of production-grade models and AI capabilities across multiple use cases, including:
  • Transaction categorization
  • Entity extraction, resolution, and enrichment
  • Income and Revenue classification
  • Fraud detection and risk scoring
  • Credit risk and credit decisioning
  • Spend propensity and customer insights
  • Personalization and predictive analytics
  • New AI-powered capabilities leveraging Open Finance and other proprietary data assets
• Partner with Product, Engineering, Sales, Risk, Marketing, and business leaders to translate customer needs into scalable data science solutions.
• Work with Sales and customers to understand market requirements, demonstrate value, and support strategic opportunities.
• Collaborate with Engineering to establish scalable production architectures, MLOps, model deployment, monitoring, and operational excellence.
• Serve as a senior thought leader and advisor to executives and key stakeholders on AI and data science applications for Open Finance.
• Build, lead, and develop a global Data Science organization, including organizational structure, technical standards, operating model, and career development framework.
• Foster a culture grounded in innovation, experimentation, scientific rigor, collaboration, and accountability for business outcomes.
• Set rigorous standards for model development, validation, monitoring, explainability, and performance.
• Ensure solutions meet applicable regulatory, privacy, security, fairness, and responsible AI requirements by partnering with Risk, Legal, and Compliance.
• Follow Mastercard’s security policies and practices, maintain confidentiality and integrity of accessed information, report suspected security violations or breaches, and complete required security trainings.

What you bring

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Engineering, Data Science, or a related quantitative discipline; advanced degree preferred or equivalent work experience.
• Experience in data science, machine learning, AI, analytics, or a related field, including significant leadership experience.
• Proven record leading and scaling large, high-performing Data Science or AI organizations.
• Deep understanding of modern machine learning and AI methods and their application to real business problems.
• Experience moving models from research and experimentation into production, commercialization, and ongoing optimization.
• Background in financial services, fintech, payments, Open Banking/Open Finance, lending, fraud, or risk is preferred.
• Strong understanding of modern data and AI platforms, MLOps, cloud technologies, and production machine learning environments.
• Strategic, pragmatic leadership to balance long-term AI innovation with near-term execution.

Tools and technologies

• MLOps, cloud technologies
• LLMs, NLP, deep learning
• Generative AI, foundation models
• Machine learning, AI

Benefits

• Insurance including medical, prescription drug, dental, vision, disability, and life insurance
• Flexible spending account and health savings account
• Paid leaves including 16 weeks of new parent leave and up to 20 days of bereavement leave
• 80 hours of Paid Sick and Safe Time
• 25 days of vacation time and 5 personal days (pro-rated based on date of hire)
• 10 annual paid U.S. observed holidays
• 401k with a best-in-class company match
• Deferred compensation for eligible roles
• Fitness reimbursement or on-site fitness facilities
• Eligibility for tuition reimbursement