As the world’s leader in digital payments technology, Visa’s mission is to connect the world through the most creative, reliable and secure payment network – enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company’s dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.
At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.
You’re an Individual. We’re the team for you. Together, let’s transform the way the world pays.
As part of the Global Product organization, the Data Products team is looking for a Data Scientist, Data Products who 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 position requires strong interpersonal skills. It 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
Independent of years of experience or educational background, successful candidates frequently have a mix of the following qualifications
Can you take on the responsibilities described above. Then please apply.
- 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 will consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.