Sr. Data Scientist US A2A Payments & Open Banking

Frankfurt, Germany

Visa

Das digitale und mobile Zahlungsnetzwerk von Visa steht an der Spitze der neuen Zahlungstechnologien für die neue Zahlung, elektronische und kontaktlose Zahlung, die die Welt des Geldes bilden

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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

As a Sr. Data Scientist, you will report to the Sr. Director of Data Science & Machine Learning and partner with risk, engineering and product to provide cutting-edge decision science to A2A payment risk. The right candidate will possess strong data science and machine learning background, with demonstrated experience in building, training, implementing and optimizing advanced ML models for payments.

The successful candidate will have experience in risk management for payments, preferably in open banking, and a solid understanding of both fraud and credit risk. They will be able to partner with product and engineering teams to scope solutions to deliver real time transaction decisioning. This role represents an exciting opportunity to make key contributions to a strategic offering for Visa. The candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.

Responsibilities:

  • Be an out-of-the-box thinker who is passionate about brainstorming innovative ways to use data to manage risk in open banking
  • Use predictive modeling and mine data from company databases and/or open banking sources to decrease payment losses while optimizing the consumer and merchant experience
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques both from external data and across the Visa network
  • Extract and understand data to improve the understanding of risk and develop visualizations to make your complex analyses accessible to a broad audience
  • Deep understanding of fraud patterns and how to systematically detect and stop fraudsters
  • Develop processes and tools to monitor and analyze model performance and data accuracy including control groups, decline inference techniques, and run time optimization
  • Partner with product and engineering to identify improvements that will reduce the loss exposure or improve the customer experience of A2A Payments
  • Support sales and account management in a consultative manner on optimizing and communicating the risk strategies for individual merchants
  • Build strong relationships with key stakeholders at the working level to execute with excellence and align closely with Visa’s risk team.

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.

Qualifications

Basic Qualifications

  • 8 years of relevant work experience with a Bachelor Degree or 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD


Preferred Qualifications

  • 9+ years of relevant work experience and a Bachelor’s Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3+ years of experience with a PhD
  • Experience in payment risk management is highly preferred and experience in open banking either in North America, United Kingdom, and/ or Europe (e.g. ACH, BACS, Faster Payments, RTP, SEPA) would be extremely helpful with preference given to US experience
  • Experience with data mining and statistical modeling such as regression, clustering techniques, decision trees, etc. is required and application to payment and/or risk use cases is preferred
  • High level of competence in SQL, Python, Spark/Scala, and Unix/Linux scripts
  • Real world experience using Hadoop and the related query engines (Hive / Impala) for big data processing
  • Ability to construct model features utilizing open-banking data, in-house data, and/or third-party data to enhance rules and models
  • Experience utilizing models and developing features for real time graphical tools and with highly complex networks is highly desired
  • Exposure to creating requirements in partnership with product and engineering teams for data science infrastructure used in real-time transaction decisioning
  • Comfort in working with agile lifecycle and/or tracking and process management tools, e.g., JIRA
  • Good business acumen and experience interpreting data to draw business insights and drive actionable strategies
  • Team oriented, energetic, collaborative, diplomatic, and flexible style
  • Demonstrated intellectual and analytical rigor with strong attention to detail

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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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Data Science Jobs

Tags: Agile Banking Big Data Clustering Credit risk CX Data Mining Engineering Hadoop Jira Linux Machine Learning ML models PhD Predictive modeling Python Scala Spark SQL Statistical modeling Statistics

Perks/benefits: Flex hours

Region: Europe
Country: Germany

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