National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Customer Insights Analyst

Hush
Clapham
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Market Data Analyst - European gas

Data Analyst

Register Your Interest - Data Analytics Director

Register Your Interest - Data Analytics Director (Basé à London)

Register Your Interest - Data Analytics Director (Basé à London)

Senior Data Analyst

CUSTOMER INSIGHTS ANALYST


Hush is an ambitious and distinctive fashion brand, with plans to double the business over the next few years. Founded 21 years ago, we are now established as one of the UK’s leading online fashion retailers. We employ around 130 employees across head office and retail, creating and selling a beautiful range of women’s clothing and accessories characterised by effortlessness, simplicity and a laidback sense of style. Despite the challenges to the retail industry, Hush has continued grow – and our company culture still reflects our entrepreneurial roots and relaxed aesthetic. We love hard-working and talented people with a can-do attitude and a passion for what they do.


THE ROLE

We are looking for an experienced and detail-orientedData Analystto join our analytics team. This role involves unlocking insights from customer, marketing, and site performance data, and providing actionable recommendations that will drive growth and optimise the customer journey. You will work closely with cross-functional teams and senior leadership, helping to shape strategies based on data. A strong background inD2C eCommerce,Advanced Google Analytics, andSQLis required, with the ability to provide training and mentorship across teams to support self-serve analytics.


RESPONSIBILITIES

  • Customer & Marketing Analytics:Perform deep dives into customer behaviour and marketing performance, focusing on segmentation, customer lifetime value, churn analysis, and conversion optimisation. You will use these insights to inform acquisition and retention strategies and optimise channel spend.
  • Advanced Google Analytics & Event Tracking:Manage and analyse data fromGoogle Analytics, setting up and optimising event tracking to measure user behaviour across the site. Experience with event measurement (e.g., page views, clicks, conversions) is critical for optimising the digital experience.
  • Attribution Modelling & A/B Testing:Implement multi-touch attribution models to evaluate the effectiveness of marketing channels. Lead A/B testing initiatives for marketing and support CRO manager, ensuring rigorous statistical analysis to derive meaningful insights that improve customer engagement and drive sales.
  • Data Reporting & Dashboards:Build and maintain robust reporting frameworks usingBI toolssuch as Tableau or Power BI, creating dynamic dashboards for marketing, product, and finance teams. You will ensure stakeholders have access to real-time data for informed decision-making and performance tracking.
  • SQL & Data Management:Use advancedSQLto extract, clean, and manipulate large datasets from various sources. Your SQL expertise, including the use of window functions, will support ad-hoc analysis, reporting, and ongoing optimisation projects.
  • Cross-Functional Collaboration:Work closely with marketing, product, e-commerce and finance teams to ensure that data-driven insights align with business goals. You will collaborate on key initiatives, such as customer journey mapping, product performance analysis, and budget optimisation.
  • Training, Upskilling, and Mentorship:Provide basic training and guidance to help cross-functional teams (e.g., marketing and product) use analytics tools to self-serve data for their needs. Upskill and mentor junior team members and stakeholders to foster a culture of data-driven decision-making across the business.
  • Data Storytelling & Senior Leadership Presentations:Synthesise complex data into clear and actionable insights that can be presented to senior leadership. Develop and present compelling narratives around customer behaviour, marketing effectiveness, and business performance to guide strategy.
  • Continuous Improvement & Innovation:Stay up-to-date with the latest trends in eCommerce and Marketing analytics and propose innovative approaches to data analysis, ensuring the company remains competitive in the premium fashion space.


THE PERSON

  • D2C eCommerce Analytics: Proven experience in analysing and optimising D2C eCommerce performance. You must have a strong understanding of customer journey metrics and the unique challenges of selling directly to consumers online.
  • Advanced Google Analytics: Deep knowledge of Google Analytics, including event tracking and custom reporting, to monitor and measure user interactions on the website and improve the overall digital experience.
  • Advanced SQL Skills: Expertise in SQL, including the ability to write complex queries using window functions, joins, and subqueries. You must be comfortable working with large datasets from relational databases, ensuring data accuracy and efficiency.
  • BI Tools: Proficiency in BI tools such as Tableau, Power BI, Looker or similar to create dashboards and visualisations for various teams, ensuring that data is accessible and actionable.
  • Attribution & A/B Testing: Strong understanding of attribution modelling and statistical principles behind A/B testing. Experience designing, executing, and analysing experiments to optimise conversion rates, marketing spend, and user experience.
  • Cross-functional Collaboration & Training: Experience working across teams to align data insights with business goals. Proven ability to provide training, mentorship, and upskilling for non-technical teams to foster self-service analytics.
  • Data Storytelling & Communication: Strong verbal and written communication skills, with the ability to translate complex data into clear, actionable insights for senior leadership and stakeholders.
  • Strong ability to work collaboratively across teams, balancing the needs of marketing, product, and finance.
  • Excellent problem-solving skills, with the ability to turn business challenges into analytical opportunities.
  • High attention to detail and organisational skills to manage multiple projects simultaneously and ensure accuracy.
  • Passion for data and a proactive approach to staying updated with the latest trends and tools in eCommerce analytics.
  • Fashion Industry Knowledge (desired but not essential): Previous experience in the fashion industry is a bonus, but a passion for premium fashion and understanding consumer behaviour is essential.
  • Additional Skills (desired but not essential): Experience with Python or R for advanced data analysis is a plus, as is knowledge of advanced statistical techniques to improve predictive modelling capabilities.


We are committed to fostering diversity, equity and inclusion in everything we do.

National AI Awards 2025

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 to Present Data Science Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

The ability to communicate clearly is now just as important as knowing how to build a predictive model or fine-tune a neural network. In fact, many UK data science job interviews are now designed to test your ability to explain your work to non-technical audiences—not just your technical competence. Whether you’re applying for your first data science role or moving into a lead or consultancy position, this guide will show you how to structure your presentation, simplify technical content, design effective visuals, and confidently answer stakeholder questions.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.