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.
As part of the Global Product organization, the Data Products team is looking for a Data Scientist, Data Products that is passionate about innovating and delivering differentiated data solutions across the Visa payment network. This person will be responsible working with the technology, product, operations and global stakeholders for application development of a product portfolio.
This is a requires strong interpersonal skills. This is critical as we interface with other specialized product groups, operations, technology, risk, analytics, marketing and corporate communications, to coordinate the build, launch and support of new and existing products.
The person should have understanding and appreciation of data engineering concepts and systems while being an expert (beyond knowledge of libraries) in data science.
- Be a standout data scientist who understands the algorithm construct at the mathematical level and not merely understanding of using available libraries
- Passionate about brainstorming innovative ways to implement data science algorithms to production environment
- Fine tune Hadoop applications for high-performance and throughput. Troubleshoot and debug any Hadoop ecosystem runtime issues
- Communicate with product partners and clients to understand the challenges they face and convince them with data
- Extract and understand data to form an opinion on how to best help our clients and derive relevant insights
- Ability to work independently and in a team to develop innovative solutions
- Develop visualizations to make your complex analyses accessible to a broad audience
- Partner with a variety of Visa teams to provide comprehensive solutions
- Find opportunities to craft products out of analyses that are suitable for multiple clients
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.
Independent of years of experience or educational background, successful candidates frequently have a mix of the following qualifications:
- 2+ year's experience in data-based decision-making or quantitative analysis
- Bachelor’s degree in computer science economics, statistics, mathematics, operations research or many others (master's degree is a plus)
- Deep knowledge of data science models.
- Strong programming skills in Python and PySpark
- Experience with Hadoop framework components (HDFS, NiFi, Spark, Scala, Presto)
- Experience with extracting and aggregating data from large data sets using Presto, Hive or other tools
- In-depth understanding of Data Structure and Algorithms
- Excellent interpersonal skills, strong verbal and written communications skills - capable of developing well-structured communications and presentations
- Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required
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.