Sr. Data Scientist

Job Description

Visa U.S.A. Inc., a Visa Inc. company, needs a Sr. Data Scientist (multiple openings) in Washington, DC to

• Provide technical leadership in a team that generates business insights based on big data, identify impactful recommendations, and communicate the findings to clients.
• Use, build and automate new predictive models to innovate and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes.
• Run projects from scoping to delivery, and engaging with internal/external partners.
• Find opportunities to craft products out of analyses that are suitable for multiple clients.
• Work with partners throughout the organization to find opportunities demonstrating Visa data to drive business solutions.
• Synthesize ideas/proposals in writing and engage in productive discussions with external or internal partners.
• Prioritize and lead multiple data science projects with diverse multifunctional partners.
• Position reports to the Washington, DC office and may allow for partial telecommuting.

Qualifications

Basic Qualifications:

• Employer will accept a Master’s degree in Statistics, Quantitative Research or related field and 4 years of experience in the job offered or in a data scientist-related occupation.
• Position requires experience in the following skills:
  • Analyzing large data sets using programming languages, such as Python, SQL, R, and/or Spark;
  • Creating data pipelines to support data ETL processes;
  • Scheduling and monitoring pipelines for data processing;
  • Designing and implementing A/B tests;
  • Designing and implementing marketing attribution models;
  • Building predictive and descriptive statistical models using machine learning, Jupyter notebooks, Python and Scala;
  • Performing statistical analysis such as Time Series, Regression, Clustering, Causal Inference and Experiment Design;
  • Applying data visualization tools to communicate findings effectively; and
  • Collaborating with cross-functional teams to develop data-driven solutions.