Data Science Manager

iO Associates
Leicester
9 months ago
Applications closed

Related Jobs

View all jobs

Data Science Lead / Manager

Data science programme lead

Data science programme lead

Data Science and Innovation Manager

Manager, Data Science - Shipping

Sr Product Manager, Data Science

Data Science Manager / Up to £100,000 / Permanent / 2 days a week onsite

We are looking for aData Science Managerto join a growingData Science teamwithin a leading eCommerce organisation. This is an exciting opportunity to drive significant commercial value in a fast-paced environment.

This role will focus on optimising how we present content to customers-ensuring the right products are surfaced at the right time and through the right channels. We are looking for a highly skilled data scientist with a strong technical foundation and excellent communication skills, combined with a passion for applying data science to real-world commercial challenges.

This is a hybrid role, offering a mix of office and remote working. The company's main headquarters are based inLeicestershire, and we welcome applicants from across the UK.

About the Role

Collaborate with teams across the business to understand challenges and own the technical solutions, identifying further opportunities to deliver value. Search optimisation - vector embedding of search terms and product items Deep learning and regression modelling for product profitability forecasts Work closely with data engineering and software development teams to define technical requirements and ensure timely delivery. Analyse large volumes of data from various sources, including transactional, demographic, and online data, to build predictive models. Apply machine learning techniques to personalise customer experiences and optimise content presentation. Design and execute robust testing strategies to validate hypotheses and measure commercial impact. Present insights and recommendations to senior stakeholders, including C-suite executives. Proactively identify opportunities for personalisation and customer experience improvements.

About You

Strong expertise in a broad range ofdata science techniques, including regression, classification, and machine learning. Experience with deep learning or generative AI is a plus but not essential. Proficiency in(Spark)SQL and Python. Experience with PySpark is beneficial but not required. Experience designing and implementing robusttesting frameworks. Strong analytical skills with keen attention to detail. Excellent communication skills-comfortable presenting insights to a variety of audiences and crafting a compelling data-driven narrative. Effective time management and ability toprioritise multiple projects. Enthusiastic and eager to learn, with a collaborative yet self-sufficient working style.

This is an exciting opportunity to play a pivotal role in shapingdata-driven customer experiencesfor aleading eCommerce business. If you're passionate about data science and looking for a role where you can make a real commercial impact, we'd love to hear from you!

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.