Visa's Global Data Science group supports bank and merchant partners by leveraging rich data sets to build creative solutions that have an immediate impact on their business and address complex problems.
Requirements
- 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, Jupyter notebooks, Python, or others.
- Presenting evidence-based insights and conveying relevant recommendations.
- 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.
- Previous exposure to financial modeling is a plus,but not required.
Responsibilities
- Use and build new predictive models to innovate and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes.
- Provide technical leadership in a team that generates business insights based on big data, identify impactful recommendations, and communicate the findings to clients.
- Be a thought leader and an expert in Risk / Auth / Fraud / Collection spaces.
- Collaborate with Risk / Auth teams on clients’ sides to guide them through Visa’s proposed solutions.
- Be an out-of-the-box problem solver who is passionate about applying data science techniques and innovate thinking to our unique data to help our clients both innovate and solve the problems they face.
- Connect with clients to understand the challenges they face and convince them with data.
- Find opportunities to craft products out of analyses that are suitable for multiple clients.
Other
- This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
- Varies upon the needs of the department.
- This position requires travel 5-10% of the time.
- 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.
- 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.
