Sr. Data Scientist - job 1 of 4

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

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. The Global Data Science group supports 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 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 (e.g., banks, merchants & retailers, digital products, marketing) with an opportunity for rotation within Data Science to gain broad exposure to Visa’s business.

Essential Functions

• Provide technical leadership in a team that generates business insights based on big data, identify actionable recommendations, and communicate the findings to clients

• Brainstorm innovative ways to use our unique data to answer business problems

• Communicate with 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

• Develop visualizations to make your complex analyses accessible to a broad audience

• Find opportunities to craft 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 solutions

• 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, and other business outcomes

• Partner with a variety of Visa teams to provide comprehensive solutions

• Synthesize ideas/proposals in writing and engage in productive discussions with external or internal stakeholders

• Provide guidance in modern analytic techniques and business applications to unlock the value of Visa’s unique data set, in keeping with market trends, client needs and emerging techniques

• Organize and manage multiple data science projects with diverse cross-functional stakeholders

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Qualifications

• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications

• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• 4+ years’ experience in data-based decision-making or quantitative analysis.
• 2+ years’ experience in Credit Risk / Fraud / Collection / Authorization analysis or related space.
• Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field.
• Analyzing large data sets using programming languages such as Python, R, SQL, Hive and/or Spark.
• Building predictive and descriptive statistical models using AI/machine learning tool kits, Jupiter notebooks, Python, or others.
• Presenting evidence based insights and conveying relevant recommendations.
• Previous exposure to financial modeling is a plus, but not required.

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

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.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 137,200.00 to 199,100.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.