Data Scientist

Cambridge
8 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist
Cambridge (1x day PW)
Up to £55,000
Health/MedTech
 
I’m supporting a long standing client in Cambridge who have had some huge success recently and need to scale their Data Science function to keep up with demand.
 
This is very much your traditional statistics focused Data Science position. I’m looking to speak to people with around 2+ years of commercial Data Science experience, heavily focused on probability and statistics.
 
You’ll be joining a genuinely lovely and talented team. It’s an opportunity to use your skills to positively impact the lives of others. Health/MedTech experience would be a nice bonus, but certainly not essential.

Responsibilities:
 
As a key member of the data science team, you’ll provide statistical expertise for clinical research, designing and refining study protocols, analysis workflows, and data pipelines. You’ll help develop advanced methodologies and visualisation tools, collaborate with clinicians to enhance statistical processes, and partner with internal and external stakeholders to deliver data-driven solutions.
 
Essential experience:

Python.
Git for version control.
Classical statistics.
Hypothesis testing (parametric and non-parametric).
Survival analysis techniques (Cox regression, etc).
Linear or logistics regression models.
Exposure to small datasets, not just large (very important). 
Desirable experience:

Familiarity with pharma/health/medical datasets.
Mixed effects models – ability to use matching techniques to create synthetic arms in clinical trials.
BSc or MSc Mathematics (statistic focus).
The office is located just five minutes from Cambridge train station, and you’ll only need to be on-site once a week (more if you wish), so it’s suitable for people who live a commutable distance from Cambridge.
 
Finally, in a world of 4-6 stage interview processes, you’ll be pleased to hear this is just 3 stages consisting of a 30 min pre screening call, one hour technical and a final culture fit interview which is done in person.
 
Reach out to Jamie Forgan for more information

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 Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.