Data Scientist

At Visa, we are passionate about making a difference. We lead the way in disrupting fraud from multiple vectors. In this role you will be joining an exciting, innovative business new to the Visa family! At Featurespace, we strive to be the world’s best software company at protecting our clients and their customers from fraud attacks. We do that with personality, heart and professionalism, cultivating an innovative, fun and positive team atmosphere where everybody can contribute to solving our clients’ problems in new, innovative ways. We are always seeking to be the best at what we do and make our customers smile. The Role In your role as Data Scientist you will help us achieve our goals and deliver success on behalf of our customers by:

• Building advanced statistical models and algorithms that infer and predict individual customer behaviours in real-time, based on retail, online and ecommerce transaction data.

Responsibilities We hire people with a willingness to adapt to a variable role, so along with the key responsibilities below, we ask for ownership of any other duties as required.

• Applying analytical theory to diverse real-world problems on large and dynamic datasets
• Generating integral work products from project kickoff through to live deployment
• Developing statistical models and algorithms for integration within Featurespace products
• End-to-end processing and modelling of large customer data sets
• Producing materials to feedback analytic output to customers (reports, presentations, visualizations)
• Working collaboratively with customers to understand the opportunities and constraints of their existing data in the context of machine learning and predictive modelling
• Evaluating and improving analytical results on live systems
• Developing an understanding of industry data structures and processes
• Working with engineering/development teams to support and enhance the analytical infrastructure
• Testing analytical models and their integration within the ARIC platform
• Providing input into future data science strategy and product development

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