Associate, Data Science , Visa Consulting and Analytics

  • Full-time
  • Job Family Group: Product Development

Company Description

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

Team Summary

To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our key bank or merchant partners and internal business units. The Global Data Science group supports these partners by using our extraordinarily rich data set that spans more than 3 billion cards globally and captures more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science and various groups at Visa. To support our rapidly growing group we are looking for Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to tackle meaningful business problems. You will join one of the Data Science teams with a core focus on developing scalable Machine Learning and A.I. based applications for clients across the Asia Pacific region.

What an Associate, Data Science does at Visa:

  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Identify and automate manual processes, optimize data delivery, re-design infrastructure for greater scalability and recurring client deliverables.
  • Extract and understand data to form an opinion on how to best help our clients and derive relevant insights
  • Develop visualizations to make your complex analyses accessible to a broad audience
  • Partner with a variety of Visa teams to provide comprehensive data solutions
  • Find opportunities to craft products out of analyses that are suitable for multiple clients

Why this is important to Visa

As payments consulting arm of Visa, VCA is growing a team of highly specialized experts who can provide best-in-class payment expertise and data-driven strategies to clients. We are building a high-performing team of data scientists, data analysts and statisticians helping major organizations adapt and evolve to meet the changes taking place in technology, finance, and commerce, with cutting-edge, creative and advanced analytic solutions. The purpose of the team is to help Visa’s clients grow their business and solve problems by providing consulting services through the use of data.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office two days a week, Tuesdays and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.


What you will need:
• 2+ years experience building end-to-end systems as a Data Scientist, ML Engineer, or Data Engineer (or equivalent)
• Bachelor’s degree in an analytical field such as computer science, data engineering, data science, econometrics, or similar others (graduate degree is a plus)
• Experience supporting model development and programming in Python or Scala
• Experience with developing and automating visualization tools, such as advanced user of Power BI, Tableau, MicroStrategy, open source tool, or similar
• Experience with extracting and aggregating data from large data sets using Hadoop, Spark, Kafka, or other tools
• Experience in automation, job scheduling, parametrizing data pipelines using Tuber, Shell scripting etc.
• Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required

Projects you will be a part of:
The nature of projects in this role will focus on creating high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows and visualizations that allow our users to derive insights from big data that in turn drive their businesses. The team will also be involved in collaborating with regional solutions and engineering teams as well as market data science teams.
• AI and ML Services: Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems. Support model development, with an emphasis on auditability, versioning, and data security. Take offline models data scientists build and turn them into a real machine learning production systems.
• Data Services: Lead development and maintenance of scalable data pipelines and build out new integrations to support continuing increases in data volume and complexity. Collaborates with data science teams to improve data models that feed client data streams and insights. Works closely with engineering teams to develop strategy for long term data platform architecture.
• Visualization Services: Lead implementation of best practices for data visualization and content development. Integrating various datasets and building data models for visualization in Tableau.

Additional Information

Visa has adopted a COVID-19 vaccination policy. As a condition of employment, all employees based in the country where this job is located are required to be fully vaccinated for COVID-19, unless a reasonable accommodation is approved or as otherwise required by law.
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