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Visa

Visa

via Lensa

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Data Scientist, AI/ML – Visa Consulting and Analytics

Anywhere
Full-time
Posted 3/6/2026
Verified Source
Key Skills:
machine learning
python
sql
federated learning
distributed systems

Compensation

Salary Range

$85K - 130K a year

Responsibilities

Develop predictive models and AI solutions to optimize business outcomes using large transaction datasets.

Requirements

Requires 2+ years experience with data science, ML, Python, SQL, and familiarity with LLMs and GenAI applications.

Full Description

About the position The Global Data Science group supports our bank and merchant partners by using our extraordinarily rich data sets that span more than 4 billion cards globally and captures more than 190 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. Responsibilities • Use and build new predictive models to innovate and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes • 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 • Leverage AI coding tools (e.g., GitHub Copilot, Claude Code, Cline, OpenAI Codex) to accelerate development • Apply data science and GenAI techniques to analyze transaction data and deliver actionable client insights • Build agentic AI systems with multi-step reasoning, tool use, and memory for complex payment decisioning workflows • Work with your data science colleagues as well as other teams across Visa to guide the critical thinking for our clients by using the data and tools available to you • Connect with clients as well as client teams regarding the results and strategic recommendations advised by your analyses • Develop visualizations to make your sophisticated analyses accessible to a broad audience • Find opportunities to craft products out of analyses that are suitable for multiple clients • Work with partners throughout the organization to explore opportunities for using Visa data to drive business solutions Requirements • 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD) • 2+ years’ experience in data-based decision-making or quantitative analysis, including exposure to LLMs and GenAI applications • Bachelor’s degree in an analytical field such as statistics, operations research, economics, computer science or many others (graduate degree is a plus) • Experience in understanding and analyzing data using Python or Other statistical software • Experience with extracting and aggregating data from large data sets using SQL, Hive, Spark or other tools • Experience and comfort with machine learning techniques and accompanying packages. • Experience with LLM orchestration frameworks (LangChain or similar), vector databases, and embedding models • Competence in Excel, PowerPoint and Tableau Nice-to-haves • 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) • Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required Benefits • 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.

This job posting was last updated on 3/11/2026

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