Data Scientist - Senior Manager, Visa Consulting and Analytics

The ideal candidates are problem solvers, equipped with strong analytical & quantitative skills suited to address key strategic needs for Visa’s clients including issuers, acquirers and merchants.

Adept at creative and critical thinking, they are able to deconstruct problems and transform insights into large scale, state-of-the-art solutions. Candidates must be quick learners with a strong sense of personal responsibility.

Responsibilities

• Develop and grow exceptional internal client relationships
• Develop and deploy analytical models and techniques within the organization and VCA’s clients
  including issuers, acquirers and merchants
• Work with large volumes of data extract and manipulate large datasets using standard tools such as Hadoop Ecosystem, SQL, PySpark, Python, ML tools, etc.
• Hands-on skills in cleaning, manipulating, analyzing, visualizing large data sets.
• Develop and validate advance data mining tools, algorithms, and other capabilities to solve business problem.
• Utilize Visa's data and analytic capabilities, technology, and industry expertise to develop, standardized and implement the consulting analytical solutions.
• Identify relevant market trends based on a deep analysis of payment industry Information. Interacting with several internal and external stakeholders for the strategic definition of analysis and initiatives.
• Continuously develop and present innovative ideas in order to improve current business practices within Visa.
• Perform client-specific analysis on portfolio data including proprietary information, such as customer demographics, activity, spend levels, fraud, credit risk and financial information.
• Communicate complex concepts and the results of the analyses in a clear and effective manner.
• Support transfer technical knowledge to facilitate implementation of the business solution provided.
• Document all projects developed and write other documentation as needed. Identify and share best practices for key topics.

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.

• BA/BS required Master's degree preferred (e.g. Statistics, Computer Science, Engineering or related fields).
• +9 years of overall experience with a preferred minimum of 4 in Banking or Payments Industry.
• Strong interest in the future of payments a must.
• Previous exposure to providing creative data science solutions in the financial services, payments industry or large merchants is a plus
• Strengths in Deep Learning, Machine Learning, Recommendation systems, Generative models, Statistical analyses
•Expertise in multiple programming languages (e.g., Python, R, Spark)
•Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn)
• Experience working with large volumes of data (Big Data) - extracting, cleaning and manipulating large datasets using standard tools such as Python/PySpark, SQL, etc.
• Knowledge of visualization tools such as Tableau or PowerBI.
• Strong project management skills and the ability to meet deadlines in a fast-moving work environment
• Possess a collaborative, diplomatic, and flexible style, with the ability to tailor communication to various audience levels
• Results oriented with strong conceptual, analytical, and problem-solving skills, with demonstrated intellectual and analytical rigor
• Exhibit intellectual curiosity and strive to continually learn.
• Ability to multi-task various projects while meeting required deadlines.
• Fluency in English (spoken/written)

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.