Sr. Data Scientist, Data Science

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in 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 while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

• 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 Required at SDS level
• 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
  
  

 Basic Qualifications

- Bachelor’s or Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field

- 6 years of work experience with a bachelor’s degree or 4 years of work experience with a Master’s degree or 2 years of work experience with a PhD degree

- Extracting and aggregating data from large data sets using SQL/Hive or Spark

- Analyzing large data sets using programming languages such as Python/R

- Developing and refining machine learning models for predictive analytics, classification and regression tasks.



Preferred Qualifications

- 10+ years of work experience with a bachelor’s degree or 8+ years of work experience with an Advanced Degree (e.g., Master’s, MBA) or 3 years of experience with a PhD

- 6+ years’ experience in data-based decision-making or quantitative analysis

- Knowledge of ETL pipelines in Spark, Python, HIVE that process transaction and account level data and standardize data fields across various data sources.

- Generating and visualizing data-based insights in software such as Tableau

- Communicating data-driven insights and conveying actionable recommendations

- Managing analytics/data science projects from scoping to delivery, and engaging with internal/external stakeholders

- Previous exposure to financial services, credit cards or merchant analytics is a plus

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.