Technical Product Analyst

Visa; Województwo mazowieckie; On-site; PLN 158,000 - 259,000; Full time

Job summary

Visa’s Risk and Security (RAS) group delivers advanced fraud detection and prevention solutions for real-time payments. The Product Analyst will translate complex fraud challenges into scalable product capabilities that protect clients and the broader payments ecosystem, working with AI data scientists, engineers, and stakeholders across regions.

This role requires strong product judgment, payments domain knowledge, and comfort with emerging AI tools to accelerate development and adoption.

Qualifications

• Experience in defining and documenting functional, nonfunctional, and technical requirements for products or services.
• Experience in utilizing project management tools to plan, execute, and monitor projects.
• Experience with AI, machine learning, predictive analytics, fraud scoring, behavioural analytics, anomaly detection, graph analytics, or transaction monitoring products.
• Understanding of real-time payments, push payments, digital payments, account-to-account transfers, card payments, or payment network ecosystems.
• Experience working cross-functional with technology teams including data science, data engineering, software engineering, platform, infrastructure, or analytics teams.
• Experience delivering small-size product features and communicating with stakeholders.

Responsibilities

• Support the product strategy and execution for AI-enabled predictive fraud intelligence capabilities across real-time push payment use cases.
• Define small scale product requirements for fraud and scam detection models, risk scores, data signals, decisioning capabilities, dashboards, and client-facing product features.
• Partner with AI data scientists, data engineers, software engineers, platform teams, and infrastructure teams to design, build, deploy, and improve fraud detection capabilities.
• Support development of capabilities for scam detection, mule activity, account takeover, suspicious beneficiary detection, behavioural anomalies, and other high-risk payment use cases.
• Work across Visa and non-Visa payment flows, helping ensure product capabilities are scalable across multiple rails, markets, clients, and integration models.
• Define and monitor success metrics, including fraud detection uplift, false positive rates, model performance, client adoption, transaction coverage, and commercial impact.
• Support pilots, client demos, product training, internal enablement, market activation, and launch readiness activities.
• Collaborate with regional, commercial, risk, legal, compliance, and client-facing teams to ensure product capabilities meet market, client, and regulatory needs.

Skills

Requirements definition

Project management

AI/ML and analytics

Cross-functional collaboration

Communication skills

Real-time payments knowledge

Small-feature delivery

Education

Bachelor's degree

Job description

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 zł157,500 - zł258,675 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

Role Summary: Visa’s Risk and Security (RAS) group delivers advanced fraud detection and prevention solutions, ensuring seamless, secure payment experiences. The Predictive Fraud Intelligence (PFI) team develops core AI/ML products within the Visa Protect suite, empowering clients to detect and prevent fraud throughout the payment lifecycle. With over 30 years of industry leadership, Visa continually evolves to meet the demands of the digital payment ecosystem.

The Product Analyst (Predictive Fraud Intelligence) will support the design, development, and delivery of advanced fraud and scam detection capabilities for real-time push payments, including both Visa and non-Visa payment flows. This role sits at the intersection of payments, AI, data science, fraud risk, and product management, and will be responsible for translating complex fraud and scam challenges into scalable product capabilities that protect clients, consumers, and the broader payments ecosystem.

The successful candidate will work closely with AI data scientists, data engineers, platform teams, product leaders, regional teams, and client-facing stakeholders to define product requirements, prioritize model and platform enhancements, and support the deployment of new predictive intelligence capabilities into live payment environments.

This is a highly cross-functional role requiring strong product judgment, payments domain knowledge, experience with AI and machine learning concepts, and the ability to lead complex initiatives from discovery through launch, adoption, and performance optimization.

All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools — for example, Claude, ChatGPT, Microsoft Copilot, or similar tools — to support everyday work, improve productivity, and accelerate product development activities.

Key Responsibilities

• Support the product strategy and execution for AI-enabled predictive fraud intelligence capabilities across real-time push payment use cases.
• Define small scale product requirements for fraud and scam detection models, risk scores, data signals, decisioning capabilities, dashboards, and client-facing product features.
• Partner with AI data scientists, data engineers, software engineers, platform teams, and infrastructure teams to design, build, deploy, and improve fraud detection capabilities.
• Support development of capabilities for scam detection, mule activity, account takeover, suspicious beneficiary detection, behavioural anomalies, and other high-risk payment use cases.
• Work across Visa and non-Visa payment flows, helping ensure product capabilities are scalable across multiple rails, markets, clients, and integration models.
• Define and monitor success metrics, including fraud detection uplift, false positive rates, model performance, client adoption, transaction coverage, and commercial impact.
• Support pilots, client demos, product training, internal enablement, market activation, and launch readiness activities.
• Collaborate with regional, commercial, risk, legal, compliance, and client-facing teams to ensure product capabilities meet market, client, and regulatory needs.
• Promote responsible use of AI and emerging technologies while ensuring appropriate consideration of privacy, security, resilience, explainability, and governance.

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

Qualifications

Basic Qualifications

• Relevant work experience and a Bachelor's degree
• Experience in defining and documenting functional, nonfunctional, and technical requirements for products or services.
• Experience in utilizing project management tools to plan, execute, and monitor projects.
• Experience with AI, machine learning, predictive analytics, fraud scoring, behavioural analytics, anomaly detection, graph analytics, or transaction monitoring products.
• Understanding of real-time payments, push payments, digital payments, account-to-account transfers, card payments, or payment network ecosystems.
• Experience working cross-functional with technology teams, including data science, data engineering, software engineering, platform, infrastructure, or analytics teams.
• Experience in supporting the development and delivery of small-size product features.
• Experience in written and verbal communication with technical and non-technical stakeholders.

Preferred Qualifications

• Experience in independently writing requirements for small-size features over a measurable period.
• Experience in responding to engineering inquiries and providing customer feedback or market data to prioritize functionality.
• Experience in contributing to the collection and quality assurance of identified metrics.
• Experience in supporting the creation of product messaging and communicating feature status to stakeholders.
• Familiarity with fraud and scam risk in real-time payments, including authorized push payment fraud, mule networks, account takeover, social engineering, suspicious beneficiaries, and unusual transaction behaviour.
• Understanding of model performance and monitoring concepts, including precision, recall, false positives, false negatives, thresholds, features, model drift, explainability, and feedback loops.
• Experience with real-time decisioning, API-based products, high-volume transaction environments, or scalable data platforms.
• Experience supporting market launches, pilots, client demos, product training, or regional enablement.

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.