Principal Data Scientist (Consultancy)

Harnham

Nottingham

7 months ago

Applications closed

Related Jobs

View all jobs

Principal, AI Data Science

Data Analyst - Aerospace

Data Analyst - Sc cleared

Principal Data Scientist

Salary: Up to £100k with a competitive bonus.

Location: UK based, 3 days a week on client site

This role is a great opportunity to work at a dynamic consultancy rooted in the UK, this firm partners closely with public agencies, retailers, transport providers, housing associations, energy companies, and healthcare systems to solve complex problems.

Shape the future of data science and AI — lead transformative projects with real-world impact. We're looking for a Principal Data Scientist to drive advanced solutions in machine learning, AI, and data analytics across diverse industries.

Key Responsibilities

Lead complex data science and AI initiatives from concept to deployment.
Develop advanced models using machine learning, optimisation, and simulation techniques.
Mentor and guide a team of data scientists, driving technical excellence.
Collaborate with clients to define problems and deliver measurable impact.
Stay hands-on with Python and modern data science tools (pandas, scikit-learn, etc.).

Requirements

Proven experience leading end-to-end data science projects.
Expertise in machine learning, statistical modelling, and optimisation.
Strong coding skills (Python, cloud platforms, ML frameworks).
Ability to communicate complex ideas to both technical and non-technical stakeholders.
Leadership experience or a desire to mentor and guide teams.
Ability to link work to commercial/performance outcomes.

Why Apply?

Meaningful work that creates real-world change.
Flexible working options and a supportive team culture.
Growth opportunities with fast-tracked career progression.

Ready to lead innovative data-driven solutions? Apply today!

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

Industry Insights

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

Apr 9, 2026

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Mar 24, 2026

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Feb 11, 2026

Careers

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.