Data Science Consultant

Datatech
London, United Kingdom
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Platform Solutions Architect (Professional Services)

Databricks London, United Kingdom

Data Platform Solutions Architect (Professional Services) - Emerging Enterprise & DNB

Databricks London, United Kingdom

Software Engineering - 12 months

Cambridge Consultants United Kingdom
Internship

Resident Solutions Architect (Professional Services)

Databricks London, United Kingdom

Head of Global Regulatory Affairs and Strategy

Isomorphic Labs Cambridge, United Kingdom

Physicist – Photonics & Optics

Cambridge Consultants United Kingdom
Posted
25 Mar 2026 (3 weeks ago)

Data Science Consultant

Datatech Analytics London Area, United Kingdom (Hybrid)

London | Manchester Hybrid

£Competitive + Bonus + Benefits

Datatech Analytics is partnering with a leading global consultancy to appoint a Data Science Consultant to join a growing Digital & Data practice.

This role sits within a multidisciplinary team of data scientists, engineers and consultants delivering advanced analytics solutions across sectors including financial services, energy, government, defence, health and consumer industries.

You will work closely with clients to translate complex business challenges into analytical approaches, building models and data-driven solutions that support better decision making.

There is particular interest in candidates with backgrounds in Operational Research and Geospatial analytics, where mathematical modelling and spatial analysis can drive insight into complex systems, optimisation challenges and real-world decision making.

The Role

As a Senior Data Science Consultant you will combine strong technical capability with consulting skills, working directly with clients to design, develop and deploy advanced analytics and machine learning solutions.

You will work across the full analytics lifecycle, from problem definition and exploratory analysis through to model development, deployment and stakeholder communication.

Typical responsibilities include:

• Designing and delivering advanced analytics, machine learning and modelling solutions

• Translating client business challenges into analytical frameworks and data-driven insights

• Developing predictive models and operational research approaches for complex decision problems

• Applying spatial or geospatial analytics where relevant to support real-world applications

• Working with cross-functional teams including product, engineering and design

• Communicating analytical approaches and findings to technical and non-technical stakeholders

Key Skills and Experience

We are looking for candidates with strong academic foundations and experience applying advanced analytics in real-world environments.

You may bring experience across:

• Data science, machine learning or statistical modelling

• Operational research, optimisation or mathematical modelling

• Geospatial analysis or spatial data modelling

• Python, SQL and data analysis tools

• Data visualisation and dashboard development

• Experience working with large datasets and cloud based analytics environments

A degree, MSc or PhD in a quantitative discipline such as data science, mathematics, operational research, physics or statistics would typically be expected.

Why This Role

This is an opportunity to work at the intersection of advanced analytics, consulting and real-world impact, helping organisations solve complex challenges through data.

You will work alongside experienced technologists, scientists and consultants on varied projects across multiple industries, while continuing to deepen your technical expertise and develop your consulting capability.

(url removed)

Eligibility for UK security clearance may be required for some projects

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.

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.

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.

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.