Decision Scientist
Your Company: NET Recruit are delighted to be partnering with an innovative and rapidly growing credit, analytics and technology organisation who are seeking a talented Decision Scientist to join their team in a full-time, permanent capacity based in the Waterloo area of London, with hybrid working available. This organisation has established itself as a leader within the consumer finance and technology sector, combining advanced analytics, machine learning and cutting-edge technology to drive intelligent decision-making and responsible lending. Operating within a collaborative, high-growth environment, they are committed to harnessing the power of data to deliver innovative solutions that improve both commercial performance and customer outcomes. The successful candidate will join an ambitious team of engineers, analysts and commercial professionals, playing a key role in developing predictive models, delivering actionable business insight and supporting strategic decision-making across the organisation. This is an excellent opportunity to join a business where innovation is encouraged, bureaucracy is minimal and your work will have a direct impact on business success.Your Roles and Responsibilities: While in this position your duties may include but will not be limited to:
- Developing and maintaining robust data solutions to support predictive modelling and advanced analytical projects
- Designing, building and deploying machine learning models to support credit risk management and wider business optimisation initiatives
- Deploying predictive models into production environments, collaborating closely with software engineering teams to deliver scalable technical solutions
- Monitoring model performance to ensure ongoing technical accuracy and commercial effectiveness
- Analysing model outputs and business performance data to generate meaningful insights and drive continuous improvement
- Conducting research and development projects to evaluate emerging technologies, data sources and modelling techniques
- Working with large, structured and unstructured datasets to identify trends, risks and commercial opportunities
- Collaborating with cross-functional stakeholders across technology, operations, legal, compliance, marketing and commercial functions
- Supporting strategic business initiatives through data-driven recommendations and analytical expertise
- Contributing towards the continuous evolution of the organisation's analytics capabilities and decision science function