Product Analyst, AI/ML Platforms
Listed on 2026-05-31
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IT/Tech
AI Engineer, Data Science Manager, Machine Learning/ ML Engineer
Job Description
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 AIP platform capabilities, working hands‑on with engineering and data science teams.
- Contribute to roadmap execution across data platforms, AI/ML lifecycle, GenAI enablement, tooling, and observability.
- Translate business, data science, and platform needs into clear user stories, requirements, and acceptance criteria.
- Lead the product requirements for platform capabilities, translating business, data science, and platform requirements into clear Features, user stories, and acceptance criteria.
- Use data and platform metrics to inform product decisions, identify gaps, and support continuous improvement.
- Collaborate effectively across product, engineering, data science, MLOps, infrastructure, and governance teams in an agile environment for faster time to market.
- Conduct product acceptance evaluations before launching to the user teams and support adoption of capabilities.
- Apply hands‑on coding skills to design and build AI/ML and Generative AI prototypes that can be evolved and deployed on scalable platform architectures.
- Remain flexible and adaptable, supporting multiple product areas and priorities as the platform evolves.
- Understand data processing concepts at scale across on‑prem and cloud environments and apply this knowledge when defining requirements and trade‑offs.
- Own end‑to‑end delivery of assigned platform initiatives from requirements through release and post‑launch validation.
- Contribute to documentation (requirements, release notes, FAQs, run books) to support stakeholders and enable smooth adoption of the AI platform.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager. 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).
- 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
- 2+ years of hands‑on experience in product management or technical product roles, ideally focused on AI/ML platforms or data‑driven products.
- Strong exposure to AI/ML and Generative AI, with experience across AI platforms, feature platforms and model workflows, Large Language Models (LLMs), evaluations, and agentic systems.
- Experienced on AIML platform on leading public cloud, AWS, Azure, GCP, Databricks.
- Hands‑on experience with GenAI prototyping, including use of APIs and basic coding (e.g., Python) to build proofs of concept or demonstrations.
- Experience with applied GenAI (e.g., OpenAI, Anthropic) for prototypes and production.
- Solid understanding of data concepts and data processing at scale, across cloud and on‑prem environments.
- Experience launching or supporting products in a highly technical, matrixed organization.
- Exposure to the payments industry or applied AI/ML use cases (fraud, risk, decisioning) or risk technology platform is a strong plus.
- Strong problem‑solving, communication, and collaboration skills.
- Proficiency with…
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