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

Apply Now

Data Analyst

Understanding Recruitment
York
6 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

📊 Data Analyst – Climate Tech | Energy Systems & Real-World Impact

Hybrid, with 2–3 days per week in their London office

I’m working with a mission-driven climate tech startup that’s building the software to help decarbonise the energy grid. Their platform already controls tens of thousands of real-world energy assets, from EVs to heating systems, shifting energy use to times when electricity is clean and cheap.


They're now hiring theirfirst Data Analystto help make sense of the millions of data points they generate each day, and to surface insights that will guide product, engineering, and commercial decisions.


Why this role could be a great fit:

  • You’ll work with real-time data from connected energy devices across the UK
  • You’ll build dashboards and reporting tools used by the whole business
  • Your work will directly support performance tracking, device monitoring, and strategic decision-making
  • This is a high-ownership role in a fast-moving, well-funded startup


You’ll work with SQL and Python, and collaborate closely with a small, cross-functional team of engineers, product managers, and energy specialists.


If you’re an ambitious analyst looking to apply your skills to real-world problems in energy and climate, this could be a great step.Let’s chat.

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

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.