Senior Data Scientist - Customer/Marketing

ASOS.com
City of London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist - National Security (TIRE) based in Cheltenham/H

Senior Data Scientist and Machine Learning Researcher

Senior Data Scientist - Customer/Marketing

Location: London, England, United Kingdom


Company Overview

ASOS is an online retailer for fashion lovers worldwide. We empower customers to be confident and offer a creative platform that impacts millions.


Job Description

We are looking for a Senior Data Scientist with expertise in causal inference and statistics to join our cross‑functional Marketing Effectiveness team. The team helps ASOS deliver the best shopping experience by employing incrementality testing and media mix modelling to understand, measure, and optimise marketing spend.


Responsibilities

  • Drive the technical development and improvement of our geo‑experimentation product used to model incremental uplift of ASOS’ digital spend.
  • Develop and enhance our media mix modelling capability that supports long‑term media planning.
  • Keep up‑to‑date with state‑of‑the‑art research, participate in reading groups, and publish novel prototypes at top conferences.
  • Continuously develop and improve code and technology, and contribute to brand‑new features for our global customer base.
  • Mentor and coach junior team members, supporting their technical progress.

Qualifications

  • Experienced Applied Scientist with hands‑on experience using causal inference techniques.
  • Experience developing geo‑experimentation frameworks or MMM models that measure digital media spend impact.
  • Knowledge or experience in retail, marketing, or ecommerce; thrives in cross‑functional platform environments.
  • Comfortable working in Python, familiar with deep learning frameworks such as TensorFlow/Keras or PyTorch, and enjoys transforming prototypes into products.

Benefits

  • Employee discount
  • ASOS Develops personal development opportunities
  • Employee sample sales
  • Access to LinkedIn learning materials
  • 25 days paid annual leave plus an extra celebration day
  • Discretionary bonus scheme
  • Private medical care scheme
  • Flexible benefits allowance (cash or other benefits)

Seniority Level

Mid‑Senior level


Employment Type

Full‑time


Job Function

Information Technology


Industries

Retail


#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

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 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.