Risk Data Science Senior 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.

The Sr Manager of Data Science is one of the risk roles in the Central Europe, Middle East and Africa (CEMEA) Data Science risk team. We are seeking an innovative and analytical thinker to champion our data-driven strategies within the region. As a Data Science Risk Manager, you will participate in building predictive and prescriptive models, and develop context-based prototypes and high-impact storyboards that promote data-driven strategies and solutions for Visa clients.

The position will primarily focus on engagements in the area of credit, fraud and operational risks, deep risk analytics, risk scoring as well as forecasting solutions.

• Work entails heavy focus on developing and implementing best-in‑class risk analytic solutions, inclusive of scoring and non‑scoring models. Create and deliver powerful insights from data through better visualization and storyboarding
• Work with a broader team that consists of Business Managers, Consultants and Data Scientists from both Visa and client organizations to strategize, co‑create, deploy and reap the benefits of data‑driven solutions
• Work with regional and global Data Science teams to develop high‑quality analytic products and solutions that promote Visa’s growth in the region
• Keep Visa at the forefront of technological advancement in Data Science by introducing cutting‑edge tools and techniques for generating business insights
• Ability to quickly understand and process alternate/non‑conventional data sources/platforms and develop AI based advanced prediction algorithms
• Develop next‑generation analytic methods where existing tools and techniques are inadequate to address business challenges
• Review, direct, guide, and inspire the analytical work of junior members in the team (Sr. Manager)
• Collaborate with internal Technology partners and Data Engineering function to best leverage Visa’s internal technology platforms, data, and the broader Visa ecosystem to support our clients’ technical data needs
• Manage workload for self and any direct reports, providing prioritization guidance for project flow to improve process efficiency
• Develop, share, and build global best practices and knowledge management within the team
• Socialize innovative ideas and approaches that are scalable and have market demand
• Champion internal requirements around Model Risk Management, Visa Analytics Rules, and Global Privacy standards around client delivery to ensure that Visa’s highly regarded market standing is maintained

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Professional

Experience:

• Minimum of 8+ years of expertise in applying Machine Learning solutions to business problems – model development and production experience required
• Post‑graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering
• Excellent knowledge, experience and understanding of quantitative techniques (modelling, statistics, root‑cause, etc.) applied to Risk Management with a focus on Card and Payments. Familiarity with key Risk and Performance Indicators.
• Experience working in one or more of the Card & Payments markets around the globe, with specific responsibilities in payments, retail banking, or retail merchant industries
• Good understanding of Payments and the Banking industry, including card verticals such as consumer credit, consumer debit, prepaid, small business, commercial and…