Portfolio Revenue & Debt Data Scientist - Thames Water

Are you ready to turn data into action and make a real impact? Thames Water is looking for a skilled and driven Portfolio Revenue & Debt Data Scientist to join our dynamic Credit Risk team. This is a unique opportunity to work at the forefront of credit risk analytics, helping to shape smarter collections strategies, reduce bad debt, and improve customer outcomes. As part of a priority investment area, you’ll play a key role in transforming how we use data—working closely with senior stakeholders, digital teams, and data owners to deliver best-in-class portfolio management.

In this pivotal role, you’ll lead deep-dive analysis into customer portfolio trends, build predictive models, and support the transition to our enterprise data lake. Your insights will directly influence operational improvements, policy decisions, and long-term financial resilience.

• Develop and maintain SQL-based reporting solutions to drive actionable insights.
• Collaborate with the Credit Reporting & Insight team to ensure analytics meet business needs.
• Partner with the Digital Team to align data governance and infrastructure.
• Work with the Income Leadership Team to shape strategy and support decision-making.
• Champion a culture of data-driven thinking across the Income function.

• Conduct root cause analysis of debt accumulation trends.
• Build and refine predictive models for credit risk and debt recovery.
• Provide insights to support the Bad Debt Transformation programme.
• Support the migration to a data lake environment, ensuring data integrity and accessibility.
• Create scalable, efficient SQL code and reporting frameworks.
• Embed analytics into strategic decision-making across the business.

To thrive in this role, you must be able to confidently answer YES to the following questions:

• Are you proficient in writing SQL queries to extract, join, and transform large datasets for MI/reporting and predictive modelling?
• Have you got experience in data cleansing, validation, and building predictive models?
• Are you proficient in Python for statistical analysis and able to relay insights to non-technical stakeholders?

In addition, you will bring:

• Proven experience in credit risk analytics, debt management, or financial modelling.
• Experience working in cross-functional teams and translating data into strategy.
• Familiarity with cloud platforms like Azure Data Lake, AWS, or Google Cloud.
• A degree (or equivalent experience) in Data Science, Mathematics, Statistics, or similar.
• A passion for continuous improvement and data-led transformation.

• Experience migrating from traditional databases to data lake architecture.
• Background in Utilities or Financial Services.
• Exposure to SAP or DM9 environments.
• Knowledge of machine learning techniques relevant to credit risk.

Location: Hybrid - Walnut Court - SN2 8BN.

Hours: 36 hours per week, Monday to Friday.

All applicants must include a covering letter describing a time when you added specific value to a project through your insight, inclusive of: metrics impacted and the results delivered.

• 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 benefits to support health, wellbeing, and finances, including annual health MOTs, physiotherapy and counselling, Cycle to Work schemes, shopping vouchers, and life assurance.

Find out more about our benefits and perks at the Thames Water careers site.

We’re the UK’s largest water and wastewater company, serving more than 16 million customers. We aim to build a better future for customers, communities, people, and the planet. Learn about our purpose and values on our careers site.

Working at Thames Water: Thames Water offers a unique, rewarding, and diverse place to work with fast-tracked career opportunities, flexible working arrangements, and excellent benefits. We welcome applications from everyone and provide extra support throughout the recruitment process as needed.

Disclaimer: Due to high application volumes, we may close the advert earlier than the advertised date, so please apply soon.