Data Science Manager

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

Principal Responsibilities 

• Evangelizes the creative use of data science to solve business problems for VFP (Visa Functions and Products), which are our Visa internal clients (e.g. Marketing, Product, Strategy and other functions)  

• Works with internal teams to drive data science business development opportunities across the organization 

• Identifies how data science and predictive techniques can be used to enhance internal and client profitability, card and payments acquisition, activation, engagement, usage and retention 

• Works with our internal teams on conducting VisaNet data science projects to drive key metrics

• Create and deliver powerful business-centric insights from data through better visualization and storyboarding 

• Collaborating with the internal partners to understand business requirements and desired business outcomes  

• Defining data science business problem scope and methodology, and creating project plans

• Executing on the project plans with appropriate data science and statistical techniques

• Ensuring project delivery within timelines

• Ensuring all project documentation is up to date, processes being followed, and all projects are reviewed per project plan

• Enhancing existing solutions and approaches by promoting new methodology and best practices in data science field

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

What we’re after…

• Graduate/Post Graduate degree (Masters or Ph.D.) in Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering or equivalent experience
• 3 - 5 years experience in data science and analytical functions
• Results oriented with strong analytical, consultative, and problem-solving skills, with demonstrated intellectual and analytical rigor
• Hands-on experience with modern distributed systems, including both Hadoop/SQL and Apache Spark
• Hands-on experience with one or more data analytics/programming tools such as Python/R
• Experience in the application of predictive modelling and machine learning technique to business problems
• Ability to communicate with impact with business audience

Preferred Qualifications

• Experience of Marketing Data Science and Analytical solutioning
• Experience working in payments industry (bank, credit reference agencies, Fintech) or management-consulting firm
• Hands on experience on processing extremely large data sets. Knowledge of payment network transactional data is a plus
• Team oriented, collaborative, diplomatic, and flexible style, with the ability to tailor data driven results to various audience levels
• Proven skills in translating analytics output to actionable recommendations and delivery
• Fluency in English

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.