Demand Reporting Data Scientist
Listed on 2026-09-05
-
IT/Tech
Data Analyst, Data Scientist
Circa £43,344 (depending on Skills & Experience)
Permanent
Full Time / 37 Hours (Flexible working opportunities available)
Huntingdon or Peterborough
- Hybrid
Double Matched Pension Scheme (up to 21% combined)
Private Healthcare
Make every drop of your potential count!
We're looking for two Demand Reporting Data Scientists to join Anglian Water's Strategic Asset Management team and help shape how consumption data is understood, reported and used across the business.
Our smart meter estate is expected to grow to 2.3 million meters by 2030, creating a rapid increase in the volume, frequency and strategic value of water consumption data. As part of our central Consumption Data Team, you'll turn this information into advanced analytical models and actionable insight that strengthen, regulatory reporting, demand management, leakage understanding and long-term water efficiency.
This is a hands‑on data science role with real operational and environmental impact. You'll work with large, high‑frequency datasets, applying statistics, predictive modelling and machine learning to improve how we calculate and understand household and non‑household consumption. You'll also help automate data preparation and reporting, retain specialist scientific capability in‑house, and support our ambition to achieve world‑leading water efficiency outcomes.
What you'll be doing:
Build and develop models that will feed directly into regulatory reporting and consumption component of the water balance, Household and Non household consumption, and night usage.
Enrich stakeholder insight of our Big Data Smart Meter set, applying quality assurance techniques and automation processes to deliver consistent reporting.
Develop statistical and predictive models that improve understanding of consumption, per capita consumption, business demand and leakage, and feed directly into regulatory reporting.
Carry out exploratory analysis, data mining and empirical analysis to identify trends, drivers and opportunities.
Apply data science techniques such as linear and multivariate regression, decision trees, Monte Carlo analysis and neural networks to complex business problems.
Define and apply performance and accuracy measures to validate models and communicate their limitations clearly.
Translate complex findings into clear visualisations and practical recommendations for operational, strategic and regulatory stakeholders.
Identify, cleanse, combine and prepare large, high-frequency datasets for analytical and data science products
Build reusable checks, automated workflows and repeatable data preparation processes
Create and maintain data pipelines, working with Data Engineers to support testing and production deployment
-Collaborate with subject matter experts, reporting teams and data squads to develop solutions that deliver measurable business value
Explore emerging data science, machine learning and artificial intelligence approaches while maintaining strong data ethics, privacy and governance standards
Stay up to date with changes to water industry regulation, reporting requirements, data protection and governance policies, and apply this knowledge to your work.
What we're looking for
A Level 5 or higher qualification in Data Science, Computer Science, Statistics, Mathematics or a related quantitative subject, or equivalent professional experience
A portfolio of data science solutions that demonstrates your approach, technical contribution and the outcomes delivered
Strong Python and SQL capability, with experience preparing, manipulating and analysing complex datasets
Practical experience applying statistical analysis, predictive modelling and machine learning techniques
Strong Power BI experience, including data discovery, semantic models, visualisation and insight communication
Experience working collaboratively in cross‑functional teams and translating business problems into analytical solutions
Strong written, verbal and visual communication skills, with the ability to explain technical approaches to non‑technical audiences
Awareness of data ethics, privacy considerations and relevant data protection requirements
Curiosity, ownership and a commitment to…
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