Collections Data Scientist

Are you ready to turn data into action? Thames Water is looking for a skilled and driven Collections Data Scientist to join our dynamic Credit Risk team.

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.

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• 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.
  

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• 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.
  
• Proficient in 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 optimisation. 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 Excel.
  

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• Prior involvement in transitioning data environments, such as migrating from traditional databases to a data lake architecture.
  
• Experience within Utilities or Financial Services.
  

Hybrid - Walnut Court - SN2 8BN.

36 hours per week, Monday to Friday.

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• Competitive starting salary of £53,910 per annum.
  
• Annual leave: 26 days holiday per year, increasing to 30 with the length of service. (plus bank holidays).
  
• Performance-related pay plan directly linked to both company and individual performance measures and targets.
  
• Generous Pension Scheme through AON.
  
• Access to lots of benefits to help you take care of you and your family’s health and wellbeing, and your finances – from annual health MOTs and access to physiotherapy and counselling, to Cycle to Work schemes, shopping vouchers and life assurance.
  

We’re the UK’s largest water and wastewater company, with more than 16 million customers relying on us every day to supply water for their taps and toilets. We want to build a better future for all, helping our customers, communities, people, and the planet to thrive. It’s a big job and we’ve got a long way to go, so we need help from passionate and skilled people, committed to making a difference and getting us to where we want to be in the years and decades to come.

Learn more about our purpose and values.

Thames Water is a unique, rewarding, and diverse place to work, where every day you can make a difference, yet no day is the same. As part of our family, you’ll enjoy meaningful career opportunities, flexible working arrangements and excellent benefits.

If you’re looking for a sustainable and successful career where you can make a daily difference to millions of people’s lives while helping to protect the world of water for future generations, we’ll be here to support you every step of the way. Together, we can build a better future for our customers, our region, and our planet.

Real purpose, real support, real opportunities. Come and join the Thames Water family. Why choose us? Learn more.

We’re committed to being a great, diverse, and inclusive place to work. We welcome applications from everyone and want to ensure you feel supported throughout the recruitment process. If you need any adjustments, whether that’s extra time, accessible formats, or anything else just let us know, we’re here to help and support.

When a crisis happens, we all rally around to support our customers. As part of Team Thames, you’ll have the opportunity to sign up to support our customers on the frontline as an ambassador. Full training will be given for what is undoubtedly an incredibly rewarding experience. It’s also a great opportunity to learn more about our business and meet colleagues.

Disclaimer: Due to the high volume of applications we receive, we may close the advertisement earlier than the advertised date. We encourage you to apply as soon as possible to avoid disappointment.