Portfolio Revenue & Debt Data Analyst

idibu; Swindon; Hybrid; GBP 40,000 - 55,000; Full time

Job summary

A leading water and wastewater company in the UK is seeking a Portfolio Revenue & Debt Data Analyst to join their Credit Risk team. In this role, you'll analyze portfolio trends, develop SQL reporting solutions, and support strategic decision-making to reduce bad debt and improve customer outcomes. Ideal candidates should have strong SQL skills and experience in credit risk analytics. Enjoy a hybrid working model and a supportive work environment with excellent benefits.

Benefits

Flexible working arrangements

Meaningful career opportunities

Excellent benefits

Qualifications

• Proficient in SQL for large datasets extraction and transformation.
• Experience in credit risk analytics and debt management.
• Ability to present complex analyses to non-technical stakeholders.

Responsibilities

• Conduct root cause analysis of debt accumulation trends.
• Develop SQL-based reporting solutions for actionable insights.
• Lead analytical projects and engage with stakeholders.

Skills

SQL proficiency

Credit risk analytics

Debt management

Data-driven insights

Stakeholder management

Education

Degree in Data Analytics, Mathematics, or Statistics

Tools

Azure Data Lake

AWS

Google Cloud

Job description

Are you ready to turn data into actionable insights and make a real impact? Thames Water is looking for a skilled and driven Portfolio Revenue & Debt Data Analyst to join our dynamic Credit Risk team.

This is a unique opportunity to work at the forefront of revenue and debt 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.

What you’ll be doing as a Portfolio Revenue & Debt Data Analyst

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

You will also:

• 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.

Key Responsibilities

• Conduct root cause analysis of debt accumulation trends.
• Deliver insights that support bad debt reduction and collections strategy.
• Lead analytical projects and manage stakeholder engagement.
• 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.

What you should bring to the role

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

• Are you proficient in writing SQL queries to extract, join, and transform large datasets for MI/reporting and predictive modelling?
• Have you previously contributed to bad debt reduction, collections strategy, credit risk decisioning, or profit & loss impact through data-driven insight?
• Have you led analytical projects and managed stakeholders?

In addition, you will bring:

• Proven experience in credit risk analytics, debt management, or financial modelling.
  Strong SQL skills for querying, reporting, and optimisation.
• Ability to translate complex analysis into clear recommendations for non-technical stakeholders.
• Familiarity with cloud platforms like Azure Data Lake, AWS, or Google Cloud.
• A degree (or equivalent experience) in Data Analytics, Mathematics, Statistics, or similar.
• A passion for continuous improvement and data-led transformation.

Desirable Experience

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

Location

Hybrid – Walnut Court – SN2 8BN

Hours

36 hours per week, Monday to Friday

Application Requirement

All applicants must include a covering letter describing a time when you added specific value to a project through your analysis, inclusive of:

• The metrics impacted
• The results delivered

Find out more about our benefits and perks

Who are we?

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.

Working at Thames Water

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.

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.

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