Data Scientist - PE Backed - Retail

twentyAI
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

twentyAI are excited to be partnered with a leading PE backed retail business in search of a Senior Data Scientist. This organisation is experiencing rapid growth, with an established national presence and ambitious expansion plans. Backed by a renowned private equity fund, this role offers a unique opportunity to spearhead data-driven projects that will directly impact critical areas such as pricing strategy, customer personalization, stock optimization, and site selection for new location


As the Senior Data Scientist, you will collaborate closely with the CTO to build the data science function and implement advanced analytics. The role is highly strategic, supporting decision-making across finance, supply chain, and marketing through data modeling and insights. This is a pivotal position for a data professional looking to make an impact on organizational growth and who aspires to lead the data science team in the future.


Key Responsibilities

  • Pricing Analytics: Develop a tool to analyze the impact of price changes on sales and revenue.
  • Personalization and Marketing: Use segmentation and customer demographics to drive targeted marketing campaigns.
  • Inventory Forecasting: Create models to optimize stock levels and ensure efficient inventory management.
  • Expansion Support: Build a property model to support the company’s growth, targeting 100+ new store locations.


Technology Stack;

  • Snowflake
  • Tableau
  • Python
  • AWS


This is a fantastic opportunity to be a part of a high growth environment with significant autonomy and the potential to scale your career into a Head of Data Science role.


This role is hybird and would expect you in the office 2 days a week

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.