At a Glance
- Tasks: Own data uploads for major retailers and optimise product visibility using AI.
- Company: MissionSwoon, a design-led brand revolutionising home trends.
- Benefits: Competitive salary, share options, bonus scheme, and 25 days annual leave.
- Other info: Remote-first role with opportunities for career development and collaboration.
- Why this job: Join a dynamic team and leverage AI to drive e-commerce success.
- Qualifications: Analytical mindset, spreadsheet skills, and a passion for e-commerce growth.
The predicted salary is between 25000 - 32000 £ per year.
MissionSwoon is an original, design‑led brand utilising an innovative NPD process to discover the next home trends. As we expand our footprint across the UK's leading retailers, we are moving away from manual data management toward a highly automated, AI‑driven trading model. We are seeking a technical, data‑native graduate to own our partner uploads for John Lewis, Next, and M&S. You do not need years of corporate experience for this role. Instead, we want raw analytical drive. You will build the automated data pipelines to ensure our listings are flawless, and you will leverage AI to ensure they actually sell.
What We Are Looking For
This is a dual‑impact graduate role combining robust data automation with forward‑thinking digital merchandising. On one hand, you are a spreadsheet wizard and automation enthusiast. You look at manual data formatting and see an opportunity to write a script, build a macro, or deploy an advanced formula to eliminate human error entirely. You have an obsessive attention to detail and believe that clean data is the foundation of good business. On the other hand, you possess deep intellectual curiosity about e‑commerce growth. You do not want a product to just be visible on a website, you want to understand exactly why it sells, or more importantly, why it doesn't and how to optimise it. You will be excited to pioneer the use of AI scraping and optimisation tools to track our digital shelf visibility, analyse competitor listings, and use data‑driven insights to maximise our conversion rates on partner platforms.
Key Responsibilities
- AI Merchandising and Digital Shelf Optimisation
- Data Automation and Partner Integration
- Automated Uploads: Own the end‑to‑end data preparation and upload process for major retail partners (John Lewis, Next, and M&S), transforming raw internal product data into platform‑ready formats.
- Pipeline Engineering: Build and maintain robust Excel templates, formulas (such as XLOOKUP, INDEX/MATCH, and dynamic arrays), or VBA and Python scripts to automate data validation.
- Rigorous Data Quality Assurance: Act as the final gatekeeper for product data. Implement foolproof validation checks to ensure zero errors in pricing, dimensions, SKUs, and imagery before sheets are submitted to partners.
- Partner Troubleshooting: Serve as the technical point of contact for partner portal errors, quickly diagnosing and resolving feed or upload discrepancies.
- Visibility Tracking: Deploy and manage AI‑driven scraping and tracking tools to monitor Swoon's actual visibility and search rankings on partner websites.
- Conversion Optimisation: Analyse how our products are displayed, identify optimisation gaps like missing search terms or poor imagery placement, and optimise copy to drive sales.
- Intellectual Competitor Intelligence: Use AI and analytics tools to benchmark our digital shelf presence against competitors, identifying emerging trends and structural gaps in partner ranges.
- Commercial Feedback Loop: Translate partner sales data and visibility metrics into actionable insights for the Design teams, ensuring we double down on what moves the needle.
Working Hours, Location and Flexibility
- Hours: 9:00 am to 5:30 pm, Monday to Friday. We have flexibility for Friday pm off if you work extra hours Monday to Thursday.
- Remote‑First: Most of the time you will be working remotely from home within the UK.
- Collaborative Workshops: We require travel to London a few times per month for workshops, and all UK train travel for these sessions will be fully expensed.
Benefits
- Competitive salary
- Share options programme
- Bonus scheme
- Wellbeing allowance
- Pension scheme (including employer contribution)
- Private medical cover for you and your family
- 25 days of annual leave + an extra day for each year of tenure
- Birthday off + an additional day for volunteering/community work
- Free furniture on each anniversary of employment
- Friends & family discount
Graduate Partner Trading and AI Merchandising Executive (UK based only) in London employer: Swoon
At MissionSwoon, we pride ourselves on being an innovative and design-led brand that values analytical drive and creativity. Our remote-first work culture fosters flexibility and collaboration, allowing you to thrive in a supportive environment while working with leading UK retailers. With competitive benefits, opportunities for personal growth, and a commitment to employee wellbeing, we are dedicated to empowering our team to make a meaningful impact in the world of e-commerce.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate Partner Trading and AI Merchandising Executive (UK based only) in London
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We think you need these skills to ace Graduate Partner Trading and AI Merchandising Executive (UK based only) in London
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Swoon, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Swoon aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
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How to prepare for a job interview at Swoon
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
