📍
Shanghai, China

Data Scientist

1 year experience
Finance
Data / Analytics
Posted:
December 29, 2025

Visa

Global digital payments and financial network
79.1
Palpable Score
Apply >view company >

Team Summary

The Global Data Science (GDS) group within Visa Consulting & Analytics (VCA) partners with markets and internal business units to turn Visa's unique data assets into insights and actions. The Internal Analytics team supports Greater China stakeholders with scalable analytics, measurement frameworks, and self-serve decision tools that enable faster, better commercial and operational decisions.

What an Analyst, Data Science does at Visa:

In this role, you will be responsible for delivering impactful analytics that influence strategic decisions across Greater China. Key responsibilities include:

Why this is important to Visa

As the payments consulting arm of Visa, VCA builds high-performing teams of data scientists and analysts to deliver best-in-class, data-driven strategies that help clients adapt to rapid changes in technology, finance, and commerce. This role strengthens our internal analytics capability for Greater China, shifting from ad-hoc requests to proactive, hypothesis-led projects that accelerate decision cycles, improve insight quality, and enable measurable business impact for Visa and its clients.

Projects you will be a part of:

These projects will give you the opportunity to shape strategic priorities, influence market growth, and work closely with senior stakeholders across Visa.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

What you will need:


• 1–3 years of analytical experience applying statistical or machine learning techniques to business problems. postgraduate degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent experience preferred.
• Hands-on experience building data pipelines and developing, validating and scaling data solutions/models.
• Proficiency in Hive/Spark/SQL and R or Python (including common ML/data packages).
• Experience building intuitive dashboards and reports in Power BI, Tableau, MicroStrategy or similar tools.
• Strong problem-solving, intellectual curiosity and results orientation. ability to manage multiple priorities while maintaining rigor and data quality.
• Strong communication skills to present insights to non-technical stakeholders.

What will also help:


• Experience in banking, payments or merchant analytics contexts. Understanding of China payments business
• Familiarity with measurement frameworks (e.g., campaign effectiveness, product benefits, event measurement).
• Experience working with cross-functional partners in market organizations and regional analytics teams.
• API & Data Integration: experience working with APIs and third party data source
• Basic business & finance knowledge
• Mandarin and English working proficiency.

About the company

Visa

Company overview
Visa is a global payments technology company that runs the network that helps move money between consumers, merchants, financial institutions, and government entities. The company provides services like authorization, clearing, and settlement that sit behind many card and digital payment experiences. Visa operates across 200+ countries and territories and works with partners ranging from banks to fintechs and large merchants. The company’s products also extend into areas like risk, fraud, data-driven services, and advisory work.

Locations and presence

Visa has major hubs in the United States (including Foster City, San Francisco, Austin, and Atlanta) alongside offices across many global regions. The company publicly positions most roles as hybrid, with examples in job postings noting set in-office days and a policy that allows short periods working from another location for eligible hybrid roles.

Palpable Score

79.1
/ 100
Visa has a broad and repeatable early-career funnel, including a global internship program and multiple structured rotational programs with clear eligibility windows. The strongest evidence sits in learning support and early-career program design, while the weaker area is end-to-end hiring transparency because public details on interview stages and feedback norms are limited.
view full company profile >

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