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

The Global Data Science group supports our bank and merchant partners by using our extraordinarily rich data sets that span more than 4 billion cards globally and captures more than 190 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. To support our rapidly growing group, we are looking for Data Scientists who are passionate about the opportunity to use Visa’s rich data to address and deliver significant results to complex problems! You will join one of the Data Science focus areas (e.g. merchants, banks) with an opportunity for rotation between Data Science teams to gain broad exposure to Visa’s business.

The role can be based in Toronto.

Essential Functions

• Use and build new predictive models to innovate and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes
• Be an out-of-the-box problem solver who is passionate about applying data science techniques and innovate thinking to our unique data to help our clients both innovate and solve the problems they face
• Work with your data science colleagues as well as other teams across Visa to guide the critical thinking for our clients by using the data and tools available to you
• Connect with clients as well as client teams regarding the results and strategic recommendations advised by your analyses
• Develop visualizations to make your sophisticated analyses accessible to a broad audience
• Find opportunities to craft products out of analyses that are suitable for multiple clients
• Work with partners throughout the organization to explore opportunities for using Visa data to drive business solutions

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 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Basic Qualifications

• 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

Preferred Qualifications

• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
• 2+ years’ experience in data-based decision-making or quantitative analysis
• Bachelor’s degree in an analytical field such as statistics, operations research, economics, computer science or many others (graduate degree is a plus)
• Experience in understanding and analyzing data using statistical software (e.g., Python, R, or others)
• Experience with extracting and aggregating data from large data sets using SQL, Hive, Spark or other tools
• Experience and comfort with machine learning techniques and accompanying packages
• Competence in Excel, PowerPoint and Tableau
• Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required

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.