Senior Staff Data Scientist - Director level - job 4 of 20

The Senior Staff Data Scientist, you will play a crucial role in building our data capabilities, collecting, analyzing, driving insights, and delivering machine learning and AI solutions that enhance our offerings. Your will play a pivotal role in building the organization’s “data muscle”, empowering teams to leverage data for smarter decisions, operational excellence and innovation. This is a unique opportunity to work in a fast-paced and startup environment where your contributions will have a direct impact.

This role represents an exciting opportunity to make key contributions to Visa's strategic vision as a world-leading data-driven company. The role requires a seasoned professional with deep expertise in data strategy, analytics, governance paired with a hands-on and scrappy mindset to deliver impactful results. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills. 

To be successful in this position, you must be highly effective working both independently and in cross-functional capacities.

Essential Functions

• Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.
• Work with product and engineering to ensure effective solutions. Deliver prototypes and production code based on need.
• Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems.
• Build needed data transformations on structured and un-structured data.
• Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, analytics, and statistical techniques.
• Devise and implement methods for efficiently monitoring model efficiency and performance in production.
• Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.
• Contribute to development and adoption of shared predictive analytics infrastructure.
• Data mining, processing and analyzing large datasets to generate insightful reports.
• Develop data modeling processes and algorithms to derive meaningful actionable insights from structured and unstructured big data
• Utilize statistical analysis, data visualization, and machine learning techniques to extract meaningful insights from datasets. Identify and interpret patterns, trends, and correlations within payment data.
• Generate comprehensive dashboards and reports for organizational leadership to use in a business setting.

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.