Portfolio Revenue & Debt Data Analyst

Overview

Job title:

Portfolio Revenue & Debt Data Analyst. . Division:
Retail.

Location:

Hybrid – Walnut Court – SN2 8BN
. Contract type:
Permanent. Full/Part-time:
Full-time.

Hours:

36 hours per week. Salary:
Competitive starting salary of £52,480 per annum. Job grade:

B. Closing date: 17/02/2026.

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.

• 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.
• 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.

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.
• 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

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

• Competitive starting salary of £52,480 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.

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