Data Science Consultant

Datatech Analytics
City of London
2 days ago
Create job alert

Data Science Consultant

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.


Eligibility for UK security clearance may be required for some projects.

Related Jobs

View all jobs

Data Science Consultant

Data Science Consultant

Data Science Consultant - Health

Data Science Consultant - Gen-AI

Data Science Consultant – Capital Markets

Data Science Consultant

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 AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.