What you will be doing
as the Collections Data Scientist: In this pivotal role, you will help shape data-led strategies that enhance customer experience and reduce bad debt, making a real impact on millions of lives across the region.
As part of a priority investment area, this is your chance to work at the forefront of Credit Risk Analytics, supporting smarter collections through advanced insight and proactive debt prevention. Working closely with a talented team and senior stakeholders, you’ll help deliver best-in-class portfolio management, drive innovation in our data capabilities, and ensure analytics are seamlessly aligned with our digital infrastructure.
Key accountabilities:
Deep dive analysis: Conduct deep-dive analysis into customer portfolio trends to identify root causes of debt accumulation, enabling preventative measures to be implemented.
Create and refine predictive models: Develop and refine predictive models and analytical frameworks to improve credit risk assessment and optimise debt recovery strategies.
Deliver bad debt improvements: Support the Bad Debt Transformation programme by providing data-led insights that drive operational improvements and policy recommendations.
Transition to the Data Lake: Support the transition to a data lake environment, allowing us to link together big data sets and unlock insights that we have not had available to us before.
Create and maintain new reporting: Develop new reporting solutions using SQL to drive actionable insights, enhancing debt management strategies.
Champion data-driven decision making: Partner with key stakeholders to embed a culture of data-driven decision-making within the Income function, ensuring analytics remain at the heart of business strategy.
What you should bring to the role:
Proven experience in credit risk analytics, debt management, or financial modelling, preferably within a collections or customer income function.
Strong background in applying data science techniques to real-world business problems, with demonstrable experience in predictive modelling and statistical analysis.
Hands-on experience with SQL for querying, data extraction, and reporting, with a focus on efficiency and maintainability.
Experience working in cross-functional teams, collaborating with stakeholders to translate complex data insights into actionable strategies.
Advanced proficiency in SQL for data querying, reporting, and optimization. Ability to write high-quality, efficient, and maintainable SQL code for queries, ensuring scalability and long-term usability.
Strong programming skills in Python and/or R for data manipulation, modelling, and visualisation.
Familiarity with cloud-based data platforms and tools, such as Azure Data Lake, AWS, or Google Cloud.
Degree, or equivalent experience, in a quantitative field such as Data Science, Mathematics, Statistics, Computer Science, or related discipline.
Strong working knowledge of Microsoft Office products, specifically MS Excel.
Desirable Experience
Prior involvement in transitioning data environments, such as migrating from traditional databases to a data lake architecture.
Experience within Utilities or Financial Services.
Location: Hybrid - Walnut Court - SN2 8BN.
Hours: 36 hours per week, Monday to Friday.
What’s in it for you?
Competitive starting salary of £44,000 per annum.
Annual leave: 26 days holiday per year, increasing to 30 with the length of service. (plus bank holidays).
Access to lots of benefits to help you take care of your and your family’s health and well-being, and your finances – from annual health MOTs and access to physiotherapy and counselling to Cycle to Work schemes, shopping vouchers and life assurance.
