Data Scientist

The Opportunity

As ourData Scientist, you will play a crucial role in helping 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. This is an exciting opportunity to collaborate with teams across the organisation to uncover opportunities to work on, share insights, and develop products.

This is a hybrid role based in our Cambridge office, so you will ideally be comfortable coming into the office once or twice a week. If you’re interested in the role but require more flexibility, please speak to us!

Day to Day

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 Coordinating work across multiple teams & when needed, taking on additional “tech lead” responsibilities for driving initiatives to completion Identifying risks and testing assumptions before development End-to-end processing and modelling of large customer data sets Leading the deployment and maintenance 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 Evangelizing on the benefits of the analytic products within Featurespace Recruiting for Data Scientists within the team Improving team processes and providing input to future team strategy  Developing a solid understanding of the fraud and financial crime industries

About you

Must haves:

Good degree in a scientific or numerate discipline, e.g. Computer Science, Physics, Mathematics, Engineering or equivalent work experience Experience using Python, Java, or another major programming language for data analysis, machine learning or algorithm development Experience leading the deployment of machine learning models into high throughput, real-time prediction contexts Commercial experience implementing statistical models and analytics algorithms in software Technical and analytical skills with the ability to pick up new technologies and concepts quickly Problem solving skills (especially in data-centric applications) Strong, clear, concise written and verbal communication skills Ability to manage and prioritise personal workload Constructive participation in system architecture/design discussions from an analytical and business impact perspective Practical experience of the handling and mining of large, diverse, data sets Experience of collaborating with multiple stakeholders on technical projects

Great to haves:

Ph.D. or other postgraduate level qualification with good mathematical background and knowledge of statistics Experience working in a Linux command line environment Experience using SQL to analyse data Experience with version control software and workflows (e.g. git) Experience mentoring junior members of a team Experience with the product development lifecycle (discovery, prototyping, implementation, iteration, sunsetting etc.) Subject matter expertise in the banking and payments industry

Equal Opportunities

Here at Featurespace we are committed to being a place of equality, inclusion and respect to provide a safe environment for you to bring your authentic self to work. We know that we gain as much strength from our differences as we do our similarities. We value diversity and are dedicated to listening and learning from each other to build and maintain a positive and productive culture. We appreciate this will be an ever-evolving focus for the business to ensure everyone feels supported and has a sense of belonging.