Data Science Manager
AI in this role
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.
Pay Transparency
The estimated salary range for a new hire into this position is €71,750 - €117,875 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, Pension, Life Insurance, Annual Leave, and Wellness Program.
Job Description
What it's all about:
Visa Consulting and Analytics (VCA) is the consulting arm of Visa, and drives tangible, impactful results for clients. Drawing on our expertise in consulting, data analytics, technology, payments and economics, VCA solves the most strategic problems for our clients. VCA's core client segments include issuers, acquirers, merchants, fintechs, payment enablers and governments.
The Intelligence & Data Solutions (IDS) team at VCA consists of data scientists, analysts, and engineers who provide analytics solutions. Their goal is to leverage VisaNet, one of the largest datasets globally, to help clients enhance their performance and increase profitability.
We are seeking a passionate and ambitious Data Science Manager to partner with Visa Consulting & Analytics (VCA) and co-develop data-driven solutions to help Visa’s clients grow their businesses.
What we expect of you, day to day:
- Develop a deep understanding of Visa’s data assets and value‑added services, and proactively translate them into compelling, commercially viable propositions that address client needs across acquisition, usage, and retention.
- Partnering closely with Sales, VCA, and Product teams to identify opportunities, shape client conversations, and convert insights into funded projects.
- Collaborate with internal and external stakeholders to define clear business problems, commercial outcomes, and success metrics, translating them into structured analytical and delivery plans.
- Execute the Data Science projects, ensuring the use of appropriate statistical and AI techniques to generate clear, business‑centric insights, supported by strong storytelling and impactful visualisation.
- Provide subject‑matter expertise and quality assurance across complex Data Science engagements, ensuring analytical rigor, relevance, and alignment with client objectives.
- Identify recurring client needs and market trends emerging from commercial engagements, and actively feed these insights into Visa’s Data Science product and solution development roadmap.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
What we'd like from you:
- Advanced analytics and AI experience applying a range of techniques (e.g., predictive modeling, machine learning, experimentation, agentic AI systems) to solve real business problems and drive measurable outcomes.
- Strong hands-on capability in data preparation and feature engineering, including cleaning, transforming, and validating large, complex datasets.
- Programming skills in Python and SQL, including production-grade data manipulation and ML workflows (e.g., pandas, scikit-learn or equivalent libraries), and the ability to work efficiently with large datasets.
- Experience designing and implementing agentic AI workflows, including multi-step reasoning pipelines, tool-augmented agents, and orchestration frameworks (e.g., LangChain, LangGraph, AutoGen, or equivalent), with the ability to evaluate agent reliability and manage failure modes in production.
- Familiarity with large language model (LLM) integration patterns, including prompt engineering, retrieval-augmented generation (RAG), function/tool calling, and memory management within agentic architectures.
- Proven ability to translate business needs into end-to-end analytical/AI solutions, from problem framing and methodology design to insight delivery and stakeholder adoption — including solutions that leverage autonomous or semi-autonomous AI agents.
- Ability to communicate complex technical concepts clearly and credibly to non-technical stakeholders, influencing decisions through storytelling, visualization, and structured recommendations.
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 welcome and encourages application from persons with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.
How we score this
Data Science Manager at Visa scores 62 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- AI Level 10 to 39
Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What's a project where you used LangChain hands-on?
- Walk me through how you've used LangGraph in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, LangChain, and LangGraph. 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.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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