Manager, Data Science & AI

• *About Us**

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.

• *Job Description**

• *Company Description**

Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team. As a global payments technology company, tech is at the heart of what we do: Our VisaNet network processes over 13,000 transactions per second for people and businesses around the world, enabling them to use digital currency instead of cash and checks. We are also global advocates for financial inclusion, working with partners around the world to help those who lack access to financial services join the global economy. Visa’s sponsorships, including the Olympics and FIFA™ World Cup, celebrate teamwork, diversity, and excellence throughout the world. If you have a passion to make a difference in the lives of people around the world, Visa offers an uncommon opportunity to build a strong, thriving career. Visa is fueled by our team of talented employees who continuously raise the bar on delivering the convenience and security of digital currency to people all over the world. Join our team and find out how Visa is everywhere you want to be.

• *Job Description and Responsibilities**

Are you skilled at turning advanced analytics and AI into real\-world, scalable business solutions? Do you enjoy deploying models and AI agents that influence customer outcomes at scale? This role focuses on **end\-to\-end AI\-driven analytics**, from problem framing and model development to **production deployment, monitoring, and business adoption**, supporting Visa’s clients and internal stakeholders.

Visa has built one of the world's most advanced payments networks. It's capable of handling more than 20,000 transactions per second, with reliability, convenience and security. With over 70 billion transactions processed by Visa every year, we have a rich source of data to help our payment industry partners plan for the future.

• *What a Manager, DS does at Visa:**

This role is primarily focused on **data science and advanced analytics**—driving insights, models, and recommendations that influence portfolio performance, customer lifecycle outcomes, and campaign effectiveness.

The role also includes **select exposure to AI and ML deployment**, where relevant, to ensure analytical solutions are scalable, production\-ready, and embedded into business decisioning.

• *Core expertise**

• Cards portfolio optimization, customer lifecycle management (CLM), and campaign effectiveness
• Strong grounding in **statistical modeling, machine learning, and data\-driven problem solving**
• Understanding of payments industry rules, data privacy, and card\-network/regulatory guidelines
• Practical expertise in **AI/ML solutioning**, including model deployment, responsible AI, GenAI/LLM awareness, and integration of AI capabilities into scalable business workflows
• *Specific responsibilities**

• Conduct deep\-dive analysis on large\-scale transactions and customer data to generate **actionable business insights**
• Build, validate, and interpret **statistical and machine learning models** (e.g., propensity, segmentation, forecasting, uplift)
• Execute the end\-to\-end analytics workflow: problem framing, data exploration, feature engineering, modeling, and validation
• Ensure analytical rigor, data quality checks, and QA on all deliverables
• Translate analytical outputs into **clear insights and recommendations** for non\-technical stakeholders
• Support the **deployment of data science models** into production environments in partnership with engineering and platform teams
• Contribute to model monitoring, performance tracking, and periodic recalibration
• Leverage AI/ML techniques where appropriate to enhance scalability, automation, or personalization use cases
• Design and support AI\-enabled solutions such as propensity engines, next\-best\-action frameworks, recommendation models, segmentation accelerators, and campaign optimization tools
• Translate AI concepts into practical client use cases, including clear problem framing, value sizing, feasibility assessment, and adoption roadmap development

• Create user\-friendly dashboards, presentations, and executive\-ready materials
• Manage multiple analytics projects simultaneously, ensuring **on\-time delivery** against the analytic plan
• Maintain accurate project documentation and support internal and client reviews
• *Innovation \& Continuous Improvement**

• Stay current with evolving analytics, ML, and AI techniques relevant to payments and consumer data
• Evaluate new data sources, tools, and methodologies that can strengthen core data science outcomes
• Share best practices and learnings across teams and markets
• *Qualifications**

• **Education \& Experience**

+ Bachelor’s degree in Economics, Finance, Computer Science, Statistics, or related quantitative field

+ **6\+ years of hands\-on experience in data science, analytics, and feature engineering**

+ Experience delivering analytics projects end\-to\-end in a fast\-paced, client\-facing environment

+ Experience supporting/owning deployment of AI/ML models in real‑world business contexts (production or pilot environments)**Technical Skills**

+ Strong proficiency in **Python** and data platforms (Hadoop, Hive, Impala, or cloud\-based equivalents)

+ Solid understanding of **statistical and ML techniques** (regression, classification, clustering, tree\-based models, etc.)

+ Familiarity with model deployment and ML lifecycle concepts is a plus, but **not the primary requirement**

+ Hands\-on exposure to AI/ML lifecycle practices, including feature stores, model registries, experiment tracking, CI/CD for models, monitoring, drift detection, and periodic recalibration

+ Working knowledge of GenAI and LLM\-enabled analytics use cases, including prompt design, retrieval\-augmented generation concepts, agentic workflows, evaluation, guardrails, and enterprise adoption considerations

+ Ability to apply responsible AI practices, including explainability, fairness, privacy, governance, human oversight, and clear documentation of model assumptions and limitations

+ Ability to explain complex analytical concepts clearly to non\-technical audiences

• *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.