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
Partner with technology, product, and governance teams to operationalize AI/ML solutions with appropriate controls, documentation, monitoring, and model risk considerations
Apply responsible AI principles (explainability, fairness, data governance) as part of model design and delivery
Stakeholder & Delivery Management
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.
Data & ML pay context
Based on 1,383 disclosed Data & ML salaries on RoleSuite, the role pays a median of $165K/year, with most offers between $128K and $210K (10th–90th percentile: $109K–$250K).
See the full Data & ML salary breakdown →