SENIOR GLOBAL MARKETING SCIENCE & AI MANAGER

We're on the lookout for individuals who are passionate about fashion, think outside the box, and have an eye for innovation.
Unleash your potential with us, and join us as we create joy and excitement in our global community to empower people to express themselves freely through fashion.

About the role 

You will build and lead Marketing Science & AI for Charles & Keith: the function that tells us what works, why, and what to do next. You will turn media, consumer, retail and product data into clear decisions on where we invest, how we show up in store and online, and which products and designs win with our customer. 

You will connect four disciplines — marketing measurement, consumer and competitive insight, omnichannel experience, and product and design analytics — into one view of the brand. You will also bring AI into how the global marketing team plans, measures and learns, so insight arrives faster and reaches every market. You will design the methods, do the analysis where it matters, and present recommendations to senior leadership. 

Responsibilities 

1. Holistic marketing activation measurement 

• Own the global measurement framework for brand and performance marketing across paid, owned, earned, retail and CRM channels. 

• Build and run marketing mix modelling (MMM) to size the contribution of each channel and market, and to guide budget allocation and scenario planning

• Design and run incrementality and lift studies (geo tests, holdouts, brand lift, conversion lift, search lift, buzz lift) to validate what drives sales and brand health

• Lead multi-touch attribution for digital journeys, and triangulate MMM, lift tests and attribution into one agreed "source of truth"

• Set the KPIs and dashboards that global and regional teams use to judge campaigns, launches and collaborations

• Turn results into clear budget and channel recommendations for the annual plan and in-flight optimisation

2. Consumer and competitive insights, analysis and strategic recommendations 

• Build a deep, data-backed understanding of our target customer: who she is, what she values, how she shops, and how this differs by market

• Run the brand health and consumer research programme (brand tracking, segmentation, U&A, concept and campaign testing) with research partners

• Monitor the competitive landscape — pricing, assortment, campaigns, channel moves and share of voice — across key markets

• Combine first-party, social listening, search, market and research data into insight that points to action

• Translate findings into strategic recommendations for brand positioning, campaigns, market entry and growth priorities, and present them to leadership

3. Omnichannel experience 

• Lead a global mystery shopping programme across stores, e-commerce and customer service, with a consistent scorecard by market

• Assess whether our retail and digital experience delivers the brand promise and resonates with our target audience

• Capture local nuances: adapt standards and research to each market's culture, shopping habits and service expectations while protecting a consistent global brand

• Map end-to-end customer journeys across store, app, web and marketplaces to find friction and moments that matter

• Link experience scores to commercial outcomes (conversion, basket size, repeat purchase, NPS) and prioritise fixes with Retail, E-commerce and Visual Merchandising teams

4. Product and design analytics 

• Measure whether our value proposition and product proposition resonate with our target audience, by category, price tier and market

• Analyse sell-through, full-price sell-through, returns, reviews and search and social demand to show which products, designs and collections perform — and why

• Run pre-launch design and concept testing to inform range building, pricing and hero product choices

• Spot emerging trends and white-space opportunities, and feed them into the product and design calendar

• Give Product, Design and Merchandising teams a regular, simple read of what is working and what to change

5. AI enablement for marketing 

• Define and deliver the AI roadmap for global marketing: use cases, tools, data needs and guardrails

• Apply AI and machine learning to forecasting, audience segmentation, personalisation, creative testing and insight generation 

• Build AI-powered tools (for example, automated reporting, insight assistants, social and review analysis) that give every market faster self-serve answers

• Partner with Data, Technology and Legal to ensure responsible, privacy-compliant use of data and AI

• Raise AI and data literacy across the marketing team through training and playbooks

Requirements 

Experience 

• 8–12 years in marketing science, analytics, consumer insights or strategy, with at least 3 years leading projects or people

• Proven hands-on experience with MMM, incrementality testing and multi-touch attribution, and with turning them into budget decisions

• Experience in fashion, luxury, beauty, retail or consumer brands; omnichannel or multi-market experience is strongly preferred

• Track record of running consumer research and mystery shopping or customer experience programmes with external agencies

• Experience applying AI or machine learning to marketing problems

Skills 

• Strong statistics and econometrics; comfortable with with BI tools 

• Working knowledge of ad platforms, analytics and measurement tools (for example, Google, Meta, TikTok, GA4, Meridian or Robyn)

• Ability to turn complex analysis into a clear story and a firm recommendation for senior, non-technical audiences

• Commercial judgement and a real interest in fashion, product and design

• Cultural awareness and comfort working across Asia, the Middle East, Europe, the U.S. and other regions

Qualifications 

• Degree in statistics, economics, data science, business, marketing or a related field; a master's degree is a plus 

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