Data Scientist

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. We support 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, Data Engineering 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 focus areas with an opportunity for rotation within the organization to gain broad exposure to Visa’s business.

The role will be based in Bengaluru, India.

Primary responsibilities

• Be an out-of-the-box thinker who is passionate about brainstorming innovative ways to use our unique data to answer business problems.
• Partner with key stakeholder/clients to understand the problem statement and convince them with data.
• Extract and understand data to form an opinion on how to best help our partners and derive relevant insights.
• Develop visualizations to make your complex analyses accessible to a broad audience.
• Find opportunities to craft solutions and products out of analyses that are suitable for multiple clients.
• Work with stakeholders throughout the organization to identify opportunities for leveraging Visa data to drive business outcomes.
• Mine and analyze data from company databases to drive optimization and improvement of product, marketing techniques and business strategies for Visa and its clients.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

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:

• Post-graduate degree or PhD in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics or Bachelors in fields such as Engineering, or equivalent.
• Minimum of 4+ years of analytics expertise in applying analytical solutions to business problems
• Proven skills in translating analytics output to actionable recommendations, and delivery of the same to key stakeholders
• Experience with extracting and aggregating data from large data sets
• Experience in understanding and analyzing data using statistical software (e.g., Python, R, SQL or others)
• Competence in Excel, PowerPoint and BI tools such as Tableau, PowerBI etc.

Preferred Qualifications:

• Experience in cards/payments, retail banking, or retail merchant industries
• Experience in presenting ideas and analysis to stakeholders
• Strategic and Functional Excellence
• A professional capacity for strong enthusiasm and accountability
• High attention to detail and quality
• Highly adaptive, comfortable working within a complex environment.
• Excellent written, verbal, and presentation communications skills appropriate for a wide, global audience.
• Strong business acumen
• Leadership and Stakeholder Management
• Strong interpersonal skills to build credibility with team members and leaders across the function as well as the organization
• Team-oriented, collaborative, and flexible, with proven ability to build strong working relationships with internal and external partners
• Self-starter who can responsibly own and advance work, take well-informed decisions, without needless delays