Level

VisaPosted 2d ago

Product Analyst

Product Analyst at Visa scores 68 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.

IN - Bengaluru, IndiamidFull time

AI in this role

openaianthropicdatabricks
ml-ops

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

Job Summary

The AI Platform Product team is building a scalable, enterprise‑grade platforms that enables teams across the organization to develop, deploy, operate, and govern AI/ML solutions at global scale. The team focuses on providing reliable, secure, and reusable platform capabilities that support the full AI/ML lifecycle - from data and feature enablement to model training, deployment, monitoring, and optimization.


The team partners closely with engineering, data science, product, and business teams to ensure AI capabilities can be delivered efficiently and responsibly across multiple use cases, including fraud, risk, authorization, and ecosystem protection.


We are seeking a hands‑on Product Analyst with experience across AI/ML platforms, data‑driven product development, and GenAI prototyping. This role is ideal for someone who is technically grounded, product‑oriented, and adaptable, and can work across multiple problem spaces as priorities evolve.


Key Responsibilities:

  • Drive and support product requirements for AI platform capabilities, partnering closely with engineering and data science teams.
  • Contribute to roadmap execution across data platforms, AI/ML lifecycle management, Generative AI enablement, developer tooling, and observability.
  • Translate business, data science, and platform needs into well-defined features, user stories, requirements, and acceptance criteria.
  • Leverage platform metrics and data insights to inform product decisions, identify gaps, and drive continuous improvement.
  • Collaborate effectively with Product, Engineering, Data Science, MLOps, Infrastructure, and Governance teams within an agile environment to accelerate delivery and time-to-market.
  • Conduct product acceptance validation prior to release and support successful adoption by user and stakeholder teams.
  • Apply hands-on technical expertise to design and develop AI/ML and Generative AI prototypes that can scale into production-ready platform capabilities.
  • Remain flexible and adaptable, supporting multiple product initiatives and evolving platform priorities.
  • Understand large-scale data processing across cloud and on-premises environments and incorporate these considerations when defining requirements and trade-offs.
  • Own end-to-end delivery of assigned platform initiatives, from requirements definition through release and post-launch validation.
  • Create and maintain product documentation, including requirements, release notes, FAQs, and runbooks, to support stakeholders and enable platform adoption.

Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:

  • 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD).

Preferred Qualifications:

  • 2+ years of experience in Product Management or Technical Product Management, preferably focused on AI/ML platforms, data platforms, or data-driven products.
  • Strong understanding of AI/ML and Generative AI technologies, including:
    • AI platforms, feature platforms, and model lifecycle workflows.
    • Large Language Models (LLMs), evaluation frameworks, and agentic AI systems.
  • Experience working with AI/ML platforms on major cloud providers, including AWS, Azure, GCP, or Databricks.
  • Hands-on experience building Generative AI prototypes using APIs and programming languages such as Python.
  • Experience leveraging industry-leading GenAI technologies (e.g., OpenAI, Anthropic) for proof-of-concepts and production solutions.
  • Solid understanding of data architecture and large-scale data processing across cloud and on-premises environments.
  • Experience launching and supporting technical products within complex, matrixed organizations.
  • Exposure to payments, fraud, risk management, decisioning systems, or risk technology platforms is highly desirable.
  • Strong analytical, problem-solving, communication, and stakeholder management skills.
  • Proficiency with software development lifecycle methodologies, version control practices, Agile delivery models, and Scrum-based development teams.

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.

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

Ml OpsOpenAIAnthropicDatabricks

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through how you've used OpenAI in your day-to-day work.
  3. What are the limits of Anthropic that you've run into, and how did you work around them?
  4. What's a project where you used Databricks hands-on?
  5. Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

  • List these exact terms on your resume: Ml Ops, OpenAI, Anthropic, and Databricks. 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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