Data Science Manager

Company Description

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.  

Job Description

The Data Solutions – Implementation and Scaling (DSIS) team sits within the Europe Data Solutions Organization and is responsible for the technical design, implementation and scaled delivery of standardized Visa Consulting & Analytics (VCA) solutions across all European markets. As a Data Science Manager within the DSIS team, you will work with stakeholders to create and deliver data-driven solutions that can be efficiently delivered to clients on a continuous basis.

Principal Responsibilities

• Drive automation of data solutions to enable efficient and repeatability revenue for VCA including:
  • Building and documenting data pipelines to prepare shared data assets for the team
  • Designing and developing visualizations and dashboards to communicate insights and client recommendations
  • Automating reproducible data extracts for client delivery
• Develop scaled methodologies that derive meaningful recommendations from data involving:
  • Advanced analytics
  • Customer segmentations
  • Predictive models
  • Client portfolio performance measurements
  • Data policy compliance requirements
• Work with VCA data scientists and consultants across Europe to support data science business development across key accounts to meet VCA revenue targets
• Promote the creative use of data science to solve business problems
• Create and deliver powerful business-centric insights from data through insightful visualization and storyboarding
• Collaborate with stakeholders to fully understand business requirements and desired business outcomes
• Handle multiple medium and long-term projects along with the rest of the team and stakeholders
• Define detailed analytic scope, methodology, and project plans
• Execute on project plans using appropriate methodologies/techniques
• Ensure project delivery within timelines and budget requirements
• Enhance existing data science solutions to incorporate new requirements or best practices
• Apply best practices to develop reproducible analytic pipelines
• Provide subject matter expertise to stakeholders

Qualifications

• Experience working in the data science, data engineering or analytics profession
• Graduate or post graduate degree (or equivalent experience) in a quantitative field such as statistics, computer science, mathematics, engineering, operational research, economics, etc
• Experience working in the payments industry (e.g. financial institutions, credit reference agencies, payment processors)
• Hands on experience working with extremely large data sets
• Team oriented, collaborative, diplomatic, and flexible style, with the ability to tailor data driven results to various audience levels
• Results oriented with strong analytical, consultative and problem-solving skills, with demonstrated intellectual and analytical rigor
• Experience planning, organizing, and managing end to end projects with diverse cross-functional teams
• Proven skills in translating analytics output to actionable recommendations
• Hands-on experience with modern distributed systems, including both Hadoop, Hive/SQL and Apache Spark
• Proficiency in creating reproducible analytic pipelines
• One or more data analytics/programming tools such as Python and R
• Proficiency with version control systems like (e.g. git, GitHub, etc)
• Data visualization using Tableau, Power BI or R/Python

Additional Information

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.