Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Team Summary

Visa Consulting & Analytics (VCA) is Visa's consulting division, serving Visa's clients (including card issuers, acquirers and merchants) and solving their strategic problems, focused on improving performance and profitability. Drawing on our expertise in strategy consulting, payments, data analytics, marketing, operational and macroeconomics, VCA drives high impact projects with tangible financial results.

What a Data Science Manager, VCA does at Visa:

The Data Science Manager is a key member of the Consulting and Analytics team, responsible for developing Data Analytics solutions to solve complex business problems by working with large data sets using quantitative techniques and building complex statistical models that learn from big data. In this highly collaborative role, you will work across multiple teams and functions to develop cutting-edge, creative, and advanced analytic solutions and processes. Together with other team members, you will design and deliver projects using appropriate analytic methodologies and techniques to address clients' business objectives, collaborating closely with business stakeholders to understand the problems and determine the most suitable analytic approaches that provide meaningful results.

The role is focused on Taiwan and will report into Analytics & Data Products lead based in Shanghai.

Responsibilities include delivering projects on time and within scope, utilizing an in-depth knowledge of data analytics and advanced data mining techniques, as well as employing AI/ML/LLM models and cloud-based analytics to help clients solve complex business problems. These analyses are essential for corroborating or refuting stated hypotheses and are incorporated into final client-facing solutions. The team continuously creates and protects analytic IP resulting from project learning.

Key Responsibilities include:

Manage and deliver analytics projects from conception to completion with actionable insights and recommendations.Clearly communicate the findings and recommendations from analysis, drive deployment and implementation of analytics solutions, and track business value impactSupport transfer technical knowledge to facilitate implementation of the business solution provided.Document all projects developed, including clear and efficient coding, and write other documentation as needed.Design, implement, and validate advanced analytics and machine learning models to address complex business challenges across Visa and its clients—including issuers, acquirers, and merchants—ensuring scalability, accuracy, and business relevance.Utilize Visa's data and analytic capabilities, technology, and industry expertise to develop, standardized and implement the consulting analytical solutions.Actively seek out opportunities to innovate by using non-traditional data and new modelling techniques fit for purpose to the needs of our clients.Work with large volumes of data, extract and manipulate large datasets using standard tools such as Hadoop (Hive), Spark, Python (pandas, NumPy), SQL, etc.Hands-on skills in cleaning, manipulating, analyzing, and visualizing large data sets.Identify relevant market trends by country, based on a deep analysis of payment industry information. Interacting with several internal and external stakeholders for the strategic definition of analysis and initiatives.Perform client-specific analysis on portfolio data including proprietary information, such as customer demographics, activity, spend levels and financial information.

Qualifications

What you will need:
• 7–10 years of relevant work experience with a bachelor’s degree, or 6+ years with an advanced degree (e.g., Master’s, MBA, JD, MD).
• Minimum of 2 years of hands-on consulting experience, with a strong understanding of client-facing project delivery and stakeholder engagement.
• Proven experience in data analytics, data science, AI, or machine learning, preferably within financial services, banking, payments, credit cards, or retail sectors.
• Deep analytical expertise in applying statistical solutions to business problems.
• Ability to integrate data from various sources for comprehensive risk assessments.
• Experience working with large-scale datasets, including data extraction and aggregation using tools such as SQL, Hive, Spark, and Python (pandas, NumPy).
• Proficiency in machine learning and statistical techniques, including Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, SVM, Clustering, and experience with ML/DL frameworks such as scikit-learn or TensorFlow.
• Excellent project management, organizational and presentational skills.
• Knowledge of Agile methodology and scrum practices.
• Ability to multi-task various projects while meeting required deadlines.
• Strong teamwork, relationship management and interpersonal skills.
• Proficient in Chinese and English (spoken/written).

What will also help:
• Proven experience in delivering growth for financial services products.
• Proven experience in Risk Management, particularly in Credit or Fraud Risk, within a Financial Institution.
• Good understanding of payments and banking.

Additional Information

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.