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Visa Inc,

Senior Data Scientist

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In-Office
London, Greater London, England
In-Office
London, Greater London, England

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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 Science Manager will support the strategy team in Europe. As a member of the data science team will need to understand tactical and strategical objectives of the strategy team, identify ways to support the team creating data science solutions, and deliver them. 

This role reports to the Strategy Data Science lead, and involves collaboration with various Visa departments to understand their requirements and create data-driven solutions.

Principal Responsibilities 

  • Evangelizes the creative use of data science to solve business problems for our internal functions (e.g. Marketing, Product, Strategy, etc.). This role will support the mainly the strategy team.
  • Works with internal teams to drive data science business development opportunities across the organisation 
  • Identifies how data science and predictive techniques can be used to enhance client profitability, card and payments portfolio management across acquisition, usage and retention 
  • Works with our internal teams on conducting VisaNet data analysis on key metrics to articulate solutions 
  • Create and deliver powerful business-centric insights from data through better visualization and storyboarding 
  • Collaborating with the internal partners to fully understand business requirements and desired business outcomes
  • Defining detailed analytic scope and methodology, and creating analytic plans 
  • Executing on the analytic plans with appropriate data mining and statistical techniques
  • Ensuring project delivery within timelines and budget requirements
  • Ensuring all project documentation is up to date and all projects are reviewed per analytic plan
  • Enhancing existing solutions and approaches by promoting new methodology and best practices in data science field




    Qualifications

    What we’re after…  

    • Graduate/Post Graduate degree (e.g. Master’s or Ph.D.) in Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering or equivalent experience
    • Results oriented with strong analytical, consultative, and problem-solving skills, with demonstrated intellectual and analytical rigor 
    • Hands-on experience with modern distributed systems, including both Hadoop/SQL and Apache Spark 
    • Hands-on experience with one or more data analytics/programming tools such as R/Python 
    • Experience in the application of predictive modelling and machine learning technique to business problems


    Preferred Qualifications 

    • Experience working in payments industry (bank, credit reference agencies, Fintech) or management-consulting firm.
    • Hands on experience on processing extremely large data sets. Knowledge of payment network transactional data is a plus
    • Team oriented, collaborative, diplomatic, and flexible style, with the ability to tailor data driven results to various audience levels
    • Proven skills in translating analytics output to actionable recommendations and delivery 
    • Fluency in English

    Additional Information

    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.

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