Head of Data Science

Wyatt Partners
City of London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Head Of Data Science

Head of Data Science - Advanced Analytics & AI

Head of Data Science, AI & Advanced Analytics

Head of Data Science, AI & Advanced Analytics Strategy

Head of Data Science - Advanced Analytics & AI

Head of Data Science, Analytics and Reporting

A Head of Data Science is the next key strategic hire for a rapid growth startup company in the retail industry with a global reach.

They have grown from 2 people to 30 people in 2 and a half years, and have seen strong revenue growth! The company are cash rich, but data strategy poor.

What’s great about this Head of Data Science role
  • You get the opportunity to develop a data science platform and a team from scratch (immediate need to hire further data scientists when you join)
  • The company is rich in untapped customer data offering huge opportunities to create value
  • You will work closely with world class engineers to develop a new data warehouse
  • Budget and bandwidth available to develop new products and services utilise the best commercial software
  • Working directly with the CMO, and also the founder of the business (an MIT grad!)
  • You will need to be a top class Statistician
  • You will likely have done a very numerate degree or master. You may even have a Quantitative PhD
  • You will have experience of working with large customer databases & datasets, and be able to give examples of the business value you have created from them
  • You will have experience of coding & software development
  • You must be excited by the opportunity to build a data science capability from scratch, and someone who is very ambitious to reach the top of their field.
  • You will be a strong communicator at all business level / strong commercial acumen

You may not be at that point yet, but this Head of Data Science role can offer the right candidate the chance to develop their career and reach a point where they are seen as a top performer & international expert in their field.

The Head of Data Science will join a company that is growing rapidly, and is already generating huge profits despite not having even reached series B funding. They may not even need it.


#J-18808-Ljbffr

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.

Careers Jobs

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.