Data Science Manager

iO Associates
Leicester
8 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager

Data Science Manager

Data Science Manager

Data Science Manager - Market Research Consultancy

Data Science Manager at Severn Trent – Coventry, England, GB

Data Science Manager (Metaheuristics)

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.