Senior Data Analyst

Auto Trader
Manchester
1 week ago
Create job alert
Overview

As a Senior Data Analyst (Product) you will have the opportunity to support building out our Consumer Growth Analytics function. You will be the authority on how the Autotrader platform is working for our users. You will work closely and seamlessly with senior stakeholders across, challenging and influencing decisions through data-informed recommendations, particularly when evaluating product changes and identifying new opportunities for improvement. You'll have the autonomy to influence and have your voice and data be heard. Youâll play a pivotal role in shaping and advancing our Product Analytics capability. A key part of your role will be to understand and communicate movements in audience metrics across our marketplace, while establishing clear governance around them. Youâll be responsible for unifying strategic and tactical perspectives to generate evidence-backed insights across our product portfolio, as well as providing consultancy to individual product teams. As a valued member of our analytics community, youâll play a key role in embedding Growth and Product Analytics principles, fostering a culture of data-driven thinking and knowledge sharing across the discipline. Youâll drive this through impactful initiatives such as training, workshops, and the development of robust frameworks that enable consistent and scalable analytics practices. You might believe that a passion for cars is a requirement, but guess what? Itâs not! At Autotrader, youâre welcome just as you are.

Note: This description preserves original language as provided.

About Autotrader

Weâre the UKâs leading automotive marketplace, a heritage brand, and a tech darling of the stock market. We bring together vehicle buyers and sellers to give them real choices. Cars may be what we're best known for but weâre also the place for pretty much everything else on wheels, from e-bikes to caravans. In the automotive world, change is a constant, thatâs why we take our job of untangling the complex car-buying journey very seriously. At our core, weâre all about people. We go our own way while embracing diversity and celebrating our differences. We dedicate ourselves to the idea that we work better together. Autotrader is a beautiful, surprising and vibrant place to work. We might not be for everyone, but we could be perfect for you.


Responsibilities
  • Deep expertise in digital ecosystems, with the ability to go beyond analytics tools (e.g., Google Analytics, Adobe Analytics) to understand the complexities of cross-platform tracking and consumer behaviour across channels.
  • Skilled at simplifying and articulating these complexities into clear, actionable insights and easy-to-digest outputs for diverse audiences.
  • Proven experience in experimentation, whether through execution or enablement, driving data-informed decision-making.
  • Experience delivering structured programs of work across teams and disciplines
  • Robust understanding of marketing influence on product performance, and the measurement frameworks used to assess impact
  • Competitor benchmarking experience, applying insights to inform strategic decisions.
  • Proficiency in SQL, Python, or R, coupled with knowledge of ETL processes and foundational data engineering principles.
  • Working knowledge of comparative statistics (eg. Bayesian, Frequentist) and predictive analytics is highly beneficial

Benefits
  • Salary of £50,000 – £70,000, plus an additional 10% of your salary awarded to you in shares each year. Shares vest in yearly instalments over the next three years; you may sell or keep them.
  • 28 days holiday per year, in addition to bank holidays and half-day closures on Christmas and New Year’s Eve.
  • Pension scheme with 7% employer contributions and 5% employee contributions.
  • Comprehensive private medical cover, enhanced family leave provisions, a car salary sacrifice scheme, share-save options, and more.
  • 24/7 online GP and dentist access, plus specialist support for assisted fertility, gender dysphoria, menopause, period care plans and related wellbeing resources.
  • Hybrid working model (Connected Working) with two fixed weekly office days for collaboration and a third day of your choice to suit work-life balance.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst (12 Month Contract)

Senior Data Analyst

Senior Data Analyst

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.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

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

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.