Data Science Manager
Indexed description
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
We are seeking a passionate and ambitious Data Science Manager to partner with Visa Consulting & Analytics 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.
- 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.
- An advanced degree (or equivalent experience) in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Experience delivering analytics/AI in payments, banking, consulting, or similarly fast-paced commercial environments.
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