Senior Data Scientist, AI/ML– Visa Consulting and Analytics

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

The Global Data Science group supports our bank and merchant partners by using our extraordinarily rich data sets that span more than 3 billion cards globally and captures more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. To support our rapidly growing scope of work capabilities at the intersection of data science, analytics and AI, we are looking for Senior Data Scientists who are passionate and leading team members and solving complex data problems using Visa rich dataset and technical toolkit. You will join one of the Data Science focus areas (e.g., merchants, issuers, enablers, fintechs) and have the opportunity to engage across the Data Science teams, providing broad exposure to Visa’s business.

Essential Functions:

• Use and build new predictive models to innovate and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes
• Provide technical leadership in a team that generates business insights based on big data, identify impactful recommendations, and communicate the findings to clients
• Leverage AI coding tools (e.g., GitHub Copilot, Claude Code, Cline, OpenAI Codex) to accelerate development.
• Be an out-of-the-box problem solver who is passionate about applying data science techniques and innovate thinking to our unique data to help our clients both innovate and solve the problems they face
• Running projects from scoping to delivery, and engaging with internal/external partners
• Develop and deploy ML pipelines, including RAG components, to deliver actionable client insights from transaction data.
• Build agentic AI systems with multi-step reasoning, tool use, and memory for complex payment decisioning workflows
• Implement GenAI evaluation methods covering quality, bias, and compliance.
• Connect with clients to understand the challenges they face and convince them with data
• Find opportunities to craft products out of analyses that are suitable for multiple clients
• Work with partners throughout the organization to find opportunities demonstrating Visa data to drive business solutions
• Synthesize ideas/proposals in writing and engage in productive discussions with external or internal partners
• Provide mentorship in modern analytic techniques and business applications, including GenAI best practices, experimentation frameworks
• Prioritize and lead multiple data science projects with diverse multi-functional partners

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Qualifications:

• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications:

• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• 4+ years’ experience in data-based decision-making or quantitative analysis, including exposure to LLMs and GenAI applications
• Degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field
• Analyzing large data sets using programming languages such as Python, SQL, Hive and/or Spark
• Building predictive and descriptive statistical models using machine learning tool kit, Jupyter notebooks, Python, or others
• Experience with LLM orchestration frameworks (LangChain or similar), vector databases, and embedding models
• Ability to present evidence-based insights and convey clear, actionable recommendations to technical and non-technical audiences
• Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer.  Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.  Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for this position is 137,200.00 to 219,700.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.