Senior Manager of Data Science

  • Ashburn, VA
  • Full-time

Company Description

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

We are currently seeking data scientist to drive analytical projects and insights for Visa Analytics. The position will be based at Visa's office in Arlington VA. Position also open to candidate in Foster City, Ca or Miami, FL.

The predictive modeling team within Visa Analytical Data Product is responsible for building and maintaining major consumer behavior models to solve business problem for clients and issuers. The team closely collaborates with other analytic stakeholders to understand the business problem in order to determine the most appropriate analytic approach that provides meaningful results to customers. Responsibilities include delivering projects on time and within scope with an in-depth knowledge of big data and cutting edge data mining techniques as well as the use of predictive, classification, machine learning and alternate analytic algorithms for modeling and segmentation.


  • Execute model implantation and performance tracking for risk models, generate performance analysis at the aggregate level, as well as issuer level.  Interpret and present performance results to non-technical audience.
  • Compile complex predictive model packages for production deployment, support model installations, and monitor and calibrate production models
  • Propel analytic product development via conducting statistical analyses on various data sources, and add values to products by being innovative and applying the analysis
  • Define financial and analytic metrics to measure development and production outcomes and produce performance reports
  • Find opportunities to create and automate repeatable analyses or build self-service tools for business users
  • Support sales and marketing efforts with sound statistical and financial analysis, execute ad-hoc analyses to meet the fast-changing market demands
  • Conduct transaction data analyses with Hadoop/Cloud and big data technologies for internal and external product owners, and develop deeper insights into the products using advanced statistical methods
  • Ensure project delivery within timelines and meet critical business needs
  • Work on cross functional teams and collaborate with internal and external stakeholders
  • Promote big data innovations and analytic education throughout the Visa organization

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 two days a week, Tuesdays and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.


Basic Qualifications
8 or more years of relevant work experience with a Bachelor Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD

Preferred Qualifications
· 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
· Graduate degree in a quantitative subject such as statistics, mathematics, economics, engineering, or similar disciplines
· 6+ year of experience in developing statistical predictive models
· Prefer modeling experience in bankcard industry or financial service company using for fraud, credit risk, bankruptcy, or marketing
. Previous experience in artificial neural network, RNN, CNN, natural language processing or graph database analytics is desirable
· Real world experience using Hadoop and the related query engines (Hive / Impala)
· High level of competence in Python, Spark and Unix/Linux scripts
· Extensive experience with SAS/SQL/Hive for extracting and aggregating data
· Hands-on experience with deep learning preferred
· Proven ability of handing multi-tasks and problem solving skill
· Demonstrated intellectual and analytical rigor, strong attention to details and excellent business writing, verbal communication, and presentation skills

Additional Information

Visa has adopted a COVID-19 vaccination policy to safeguard the health and well-being of our employees and visitors. As a condition of employment, all employees based in the U.S. are required to be fully vaccinated for COVID-19, unless a reasonable accommodation is approved or as otherwise required by law.

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.

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