Data Scientist

Data Scientist - Skip Rates

Location: Wokingham (Hybrid - 2-3 days per week on site)Contract: Initial 6 months (Full time)Day Rate: From £650 per day (via Umbrella)

About the Role Our client, a leading organisation at the heart of the UK energy system, is seeking an experienced Data Scientist to join their Skip Rate Team within System Operations.

This is an exciting opportunity to contribute to one of the energy industry's most high-profile challenges - improving transparency around dispatch skip rates within the Balancing Mechanism. You'll play a key role in analysing and modelling large datasets to identify the drivers of skips, developing monitoring tools, and supporting data-led solutions that enhance system transparency.

You'll collaborate closely with operational experts, data specialists, and external stakeholders across the wider energy market to ensure fair, consistent, and data-driven outcomes.

Key Responsibilities

• Analyse and model large datasets to identify factors influencing skip rates.
• Develop and enhance methodologies, tools, and reporting processes.
• Use data insights to drive consistency and transparency in dispatch operations.
• Present findings clearly to technical and non-technical audiences.
• Support wider transparency and engagement initiatives across the organisation.

About You

• Strong analytical and data science background with experience managing large datasets.
• Proficiency in analytical tools such as Python, R, SQL, or Power BI.
• Excellent communication skills - able to explain complex data in a simple, impactful way.
• Experience collaborating across technical and operational teams.
• Knowledge of the UK energy market, system operation, or balancing mechanism advantageous.

Is this of interest? If so, apply now with an up-to-date CV for consideration!

Note - if you do not hear back within 48 hours of applying, please assume you have been unsuccessful on this occasion, however, we will have your CV and contact details on files should something more suitable arise.

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