Data Scientist

Sheffield
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Role: Data Scientist
Location: Hybrid, one day a week in Sheffield
Salary: Between £40-60k
Not all Data Scientist roles are equal – you know this. Some involve working in large, slow-moving companies that are trying to pivot to AI and ML. They’re OK, but they’re just soooo slooooow.
Others involve working in excitable, fast-moving start-ups where the tech and culture are amazing, but you’re only ever a month away from potentially losing your job…or getting promoted! The future is just too uncertain for your liking (and your rent/mortgage/Deliveroo payments)
Then there are roles with companies like the one we are recruiting for. An established, profitable young business who have struck a goldmine of an idea, and already have customers queuing up to sign on the dotted line.
They have developed a data-led product that is going to revolutionise their sector, and the orders are coming in thick and fast from major global players who they’ve worked with for years.
You’ll be joining a new data science team that is likely to grow further over the next 12 months.
The role will involve using various statistical / machine learning techniques to drive insights from large, complex datasets on behalf of their customers.
You’ll need to be a dab-hand at data analysis and visualisation, and will likely have used Python, R and SQL in your current or previous roles.
Any exposure to ML models and/or Cloud tools such as Azure Databricks would be advantageous.
The role would be based mainly from home with travel into Sheffield once a week, so ideally you will drive.
If this sounds like something worth discussing further, apply or get in touch with us at Rebel Recruiters!
The company are likely to grow further, so if you are an experienced data scientist who would prefer a more senior role please apply anyway stating your salary expectations.
Please note: All UK-based applicants will be given a guaranteed reply.
We welcome diverse applicants and are dedicated to treating all applicants with dignity and respect, regardless of background

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 to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

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.