Data Scientist - Renewable Energy

Selby
5 days ago
Create job alert

Data Scientist - Renewable Energy

3-Month contract - Inside IR35 - market rate

Selby based - hybrid working - 1/2 days office based

Must have previous experience in energy sector, power generation or power trading industry

Key Responsibilities

Partner with business stakeholders to identify and prioritise opportunities where data science can deliver measurable value.
Collect, clean, and transform structured and unstructured data from multiple internal and external sources.
Develop, test, and deploy predictive models and machine learning algorithms to address business challenges.
Conduct exploratory data analysis (EDA) to uncover trends, patterns, anomalies, and key drivers.
Communicate insights and recommendations through clear storytelling, visualisations, and dashboards.
Collaborate with engineering teams to productionise models and ensure reliability, scalability, and ongoing performance.
Evaluate model accuracy and effectiveness, implementing continuous optimisation and tuning.
Stay up to date with emerging data science tools, methodologies, and industry best practices.
Perform sensitivity analysis to assess model robustness and variable impact.

Required Skills and Qualifications

At least 5 years' experience in client‑facing data science roles with demonstrable impact on business outcomes.
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
Strong proficiency in Python or R, including libraries such as pandas, scikit‑learn, NumPy, TensorFlow, or PyTorch.
Solid understanding of statistical analysis, hypothesis testing, and experimental design.
Hands‑on experience applying a range of supervised and unsupervised machine learning techniques (e.g., Random Forest, regression models, clustering methods).
Proficiency with SQL and data warehousing technologies.
Ability to translate complex analytical findings into clear, practical business recommendations.
Strong problem‑solving skills and natural curiosity for exploring and understanding data.
Industry experience in power generation and power trading

Preferred Skills and Qualifications

Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
Background in deploying machine learning models into production environments (MLOps experience is advantageous).
Hands‑on experience with big‑data or distributed computing tools such as Spark and Databricks.
Familiarity with visualisation tools such as Power BI, Tableau, or Plotly.

Key Competencies

Strong analytical and conceptual thinking.
Excellent communication and data‑storytelling capabilities.
Effective collaboration and stakeholder‑engagement skills.
High attention to detail and commitment to data accuracy.
Continuous learning mindset and openness to new techniques and technologies.Disclaimer:

This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist Placement

Data Scientist (NLP & LLM Specialist)

Data Scientist - Renewable Energy

Data Scientist - Supply Chain Optimisation

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.

How Many Robotics Tools Do You Need to Know to Get a Robotics Job?

If you’re pursuing a career in robotics, it can feel like the list of tools you should learn never ends. One job advert asks for ROS, another mentions Gazebo, another wants experience with Python, Linux, C++, RobotStudio, MATLAB/Simulink, perception stacks, control frameworks, real-time OS, vision libraries — and that’s just scratching the surface. With so many frameworks, languages and platforms, it’s no wonder robotics job seekers feel overwhelmed. But here’s the honest truth most recruiters won’t say explicitly: 👉 They don’t hire you because you know every tool — they hire you because you can apply the right tools to solve real robotics problems reliably and explain your reasoning clearly. Tools matter — but only in service of outcomes. So the real question isn’t how many tools you should know, but which tools you should master and why. For most robotics roles, the answer is significantly fewer — and far more focused — than you might assume. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable, confident, and ready to contribute from day one.

What Hiring Managers Look for First in Robotics Job Applications (UK Guide)

Robotics is one of the most dynamic, interdisciplinary fields in technology — blending mechanical systems, embedded software, controls, perception (AI/vision), modelling, simulation and systems integration. Hiring managers in this space are highly selective because robotics teams need people who can solve real-world problems under constraints, work across disciplines, and deliver safe, reliable systems. And here’s the reality: hiring managers do not read every word of your CV. Like in many tech domains, they scan quickly — often forming a judgement in the first 10–20 seconds. In robotics, those first signals are especially important because the work is complex and there’s a wide range of candidate backgrounds. This guide unpacks exactly what hiring managers look for first in robotics applications and how to optimise your CV, portfolio and cover letter so you stand out in the UK market.

The Skills Gap in Robotics Jobs: What Universities Aren’t Teaching

Robotics is no longer confined to science fiction or isolated research labs. Today, robots perform critical tasks across manufacturing, healthcare, logistics, agriculture, defence, hospitality and even education. In the UK, businesses are embracing automation to improve productivity, reduce costs and tackle labour shortages. Yet despite strong interest and a growing number of university programmes in robotics, many employers report a persistent problem: graduates are not job-ready for real-world robotics roles. This is not a question of intelligence or dedication. It is a widening skills gap between what universities teach and what employers actually need in robotics jobs. In this article, we’ll explore that gap in depth — what universities do well, where their programmes often fall short, why the disconnect exists, what employers really want, and how you can bridge the divide to build a thriving career in robotics.