Graduate Partner Trading and AI Merchandising Executive

This technical graduate role focuses on using advanced Excel, scripting, and AI-driven scraping tools to build automated data pipelines for major retail partner platforms while optimizing e-commerce listings to maximize digital shelf visibility and conversion rates.

Description

The Mission

Swoon 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

1. 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: Move us away from manual data entry by building and maintaining 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.

2. AI Merchandising and Digital Shelf Optimisation

• 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: Drive performance rather than just pushing listings live. 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.

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

• Your birthday off + an additional day for volunteering/community work

• Free furniture on each anniversary of employment

• Friends & family discount