Job Description 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 Opportunity As a Data Scientist you will help us achieve our goals and deliver success on behalf of our customers by developing and maintaining the end-to-end analytic products that exist within our Solutions, including data schemas, advanced statistical models, reporting configuration, and documentation. You will collaborate across the organisation with commercial, product, delivery, and engineering team to uncover opportunities to work on, share insights, and develop products. 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. Interacting with users (both internal and external) to understand their problems and sharing this insight with the rest of the team. Collaborating with Product Managers & other members of the team to align on the highest value items to work on Identifying risks and testing assumptions before development End-to-end processing and modelling of large customer data sets Deploying and maintaining of statistical models and algorithms Testing analytical models and their integration within the Featurespace platforms Ensuring high quality documentation exists alongside analytics products (reports, presentations, visualizations) Measuring, documenting, and improving outcomes associated with analytic products. Supporting the delivery teams delivering analytic products. Enabling both technical and non-technical colleagues by effectively communicating insights learnt during discovery and data analysis. Improving team processes and providing input to future team strategy Mentoring more junior members of the team as well as managing and prioritising their workload to ensure high-quality output. Developing a solid understanding of the fraud and financial crime industries This is a hybrid role, requiring three days per week in our Cambridge office.