Head of Data Science & Predictive Modeling

Company Description

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

The Risk and Identity Solutions (RaIS) strategy is to enable our clients to accelerate revenue growth through approval optimization and risk solutions delivered across the payment ecosystem and agnostic to type or channel. Delivering modern modular solutions, designed around customer personas, and enabled by a single flexible architecture. This strategy is underpinned by foundational capabilities in data, data science and advanced predictive modelling.   

 

The Head of Data Science and Predictive Modeling will lead the strategy for portfolios including, Visa Advanced Authorization, Risk-Based Authentication, Visa Deep Authorization, Decision Manager and Visa Consumer Authentication. They will drive best-in-class data science and modeling practices to evolve existing products and models to better support Visa’s customers. They will understand the importance of MLOps and emerging best practices in managing data platforms, tools and teams at scale. This leader will effectively lead highly technical teams, and drive innovation, centralization, and horizontal integration while partnering with peers at the SVP level to align on commercial priorities enabled by this team.  

 

To that end, the incumbent will need to be a seasoned leader of large data science and modeling teams, with a product leadership mindset, and strong commercial and financial acumen. The incumbent will have managed and/or owned end-to-end delivery of sophisticated models, and is experienced with high performance, high velocity, low latency environments and models. The Head of Data Science and Modeling will be a change champion, enabling teams to use new strategies and tools to optimize outcomes. To that end, the incumbent must understand, and have a clear perspective on, the interlinkage between data, models, scores, rules, and orchestration to optimize performance in a fraud/analytical environment for high velocity, low latency transactions. 

 

As a product executive, the candidate must have a proven history of managing risk-based products and teams through phases of a product’s lifecycle – from concept through management and ultimately sunset is essential. In addition to real-world experience and instinct, they should have the ability to leverage well-structured empirical and financial artifacts to support their business plans and strategy.  

 

Strong interpersonal skills and the ability to build great relationships, generate consensus, and promote excitement and enthusiasm while evangelizing highly technical topics to a wide audience are critical qualities for success.

Qualifications

BASIC QUALIFICATIONS

Minimum of Master’s degree. Advanced degree preferred.

Experience leading large multi-functional teams through data science, software development and commercialization efforts,

12+ years’ experience in data science and modelling, including leading large teams (100+)

Strong commercial and financial acumen

Experience implementing strong product governance disciplines within diverse teams.

Experience managing/owning end-to-end delivery of sophisticated models

Experience with high performance, high velocity, low latency environments and models which are mission critical.

Experience modernizing and re-platforming mission-critical models and introducing new approaches to MLOps.

Understanding of the interlinkage between data, models, scores, rules, and orchestration in a fraud/analytical environment.

Experience with co-development and bespoke model development at scale with large customers.

Understanding payments, fraud and authentication landscape and ability to translate product strategy into executable plans.

Able to build relationships and gain exposure to internal and external client leadership teams through demonstrating key domain expertise.

Very strong communication and influencing skills.


PREFERRED QUALIFICA