Vice President, Data Scientist (Open Finance)

Mastercard is hiring a Vice President, Data Scientist (Open Finance) in New York, United States. Level rates it ; you can apply on Level.

AI in this role

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Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Vice President, Data Scientist (Open Finance)

Overview

We are seeking an experienced and visionary Vice President of Data Science – Open Finance to lead the development, and delivery of advanced data science and AI capabilities that power our Open Finance business.

This people leader will be responsible for building and scaling a world-class Data Science organization focused on transforming financial data into actionable insights, predictions, and decisioning capabilities. The role will span foundational data intelligence and high-value applications including transaction categorization, entity extraction, income and revenue classification, fraud detection, credit risk, propensity modeling, and other AI-powered financial insights.

The VP will work closely with their immediate team and senior leaders across Product, Engineering, Sales, Privacy and other business functions to identify high-value opportunities, translate business problems into data science solutions, and deliver capabilities that create measurable customer and commercial value.

The ideal candidate combines deep expertise in modern data science and AI with strong product acumen and a track record of scaling teams and production-grade machine learning solutions.

Role

Data Science Strategy
- Define and execute the Data Science strategy for Open Finance in alignment with overall business and product objectives.
- Identify opportunities where advanced analytics, machine learning, and AI can create differentiated products, improve decisioning, reduce risk, and drive growth.
- Establish a scalable roadmap spanning foundational intelligence capabilities and application-specific models and solutions.
- Evaluate and adopt the latest advances in machine learning, generative AI, foundation models, LLMs, deep learning, NLP, and other emerging technologies where they can create meaningful business value.

Data Science Products & Solutions
- Ensure models are accurate, scalable, explainable where required, resilient, and continuously improved based on performance and changing market conditions.
- Lead the development and continuous improvement of production-grade models and AI capabilities, 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 that leverage Open Finance and other proprietary data assets

Cross-Functional Leadership
- Partner closely with Product, Engineering, Sales, Risk, Marketing, and business leaders to understand customer needs and translate them into scalable data science solutions.
- Work directly with Sales and customers to understand market requirements, demonstrate the value of AI-powered capabilities, and support strategic opportunities.
- Collaborate with Engineering to establish scalable production architectures, MLOps practices, model deployment, monitoring, and operational excellence.
- Serve as a senior thought leader and trusted advisor to executives and key stakeholders on the application of AI and data science to Open Finance.

Organizational Leadership
- Build, lead, and develop a high-performing global Data Science organization.
- Establish the appropriate organizational structure, technical standards, operating model, and career development framework for the team.
- Attract, retain, and develop world-class data science and AI talent.
- Foster a culture of innovation, experimentation, scientific rigor, collaboration, and accountability for business outcomes.
- Establish strong partnerships between Data Science, Product, and Engineering, with clear ownership and shared objectives.

Model Governance & Responsible AI
- Establish rigorous standards for model development, validation, monitoring, explainability, and performance.
- Ensure solutions meet applicable regulatory, privacy, security, fairness, and responsible AI requirements.
- Partner with Risk, Legal, Compliance, and other control functions to ensure appropriate governance for AI and machine learning solutions.

All About You

- 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.
- Previous experience in data science, machine learning, AI, analytics, or a related field, with significant leadership experience.
- Proven experience leading and scaling large, high-performing Data Science or AI organizations.
- Deep understanding of modern machine learning and AI techniques and their application to real-world business problems.
- History taking machine learning models from research and experimentation through production, commercialization, and ongoing optimization.
- Background in financial services, fintech, payments, Open Banking/Open Finance, lending, fraud, or risk preferred.
- Strong understanding of modern data and AI platforms, MLOps, cloud technologies, and production machine learning environments.
- Strategic and pragmatic: able to balance long-term AI innovation with near-term execution.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

Abide by Mastercard’s security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, 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; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.THIS POSTING IS NOT FOR A CURRENT VACANCY, BUT MASTERCARD IS SEEKING RESUMES TO REVIEW IN THE FUTURE WHEN JOBS BECOME AVAILABLE.

Pay Ranges

New York City, New York: $244,000 - $390,000 USD

Purchase, New York: $233,000 - $374,000 USD

How we rate this

Vice President, Data Scientist (Open Finance) at Mastercard rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Vice President, Data Scientist (Open Finance) is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in New York City, New York.
The job was posted on October 7, 2026.
Seniority: executive.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsNLPAI Safety

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
What NLP problem have you worked on, and how did you measure whether it actually worked?
How do you think about the risk of an AI system in this kind of role failing silently?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ML Ops, NLP, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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