Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist

Wokingham
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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.

Adecco is an employment consultancy. We put expertise, energy, and enthusiasm into improving everyone's chance of being part of the workplace. We respect and appreciate people of all ethnicities, generations, religious beliefs, sexual orientations, gender identities, and more. We do this by showcasing their talents, skills, and unique experience in an inclusive environment that helps them thrive

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.