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Manager – Product Analytics - Fashion Ecommerce

Job in Dubai, Dubai, UAE/Dubai
Listing for: Landmark Group
Full Time position
Listed on 2026-01-14
Job specializations:
  • IT/Tech
    Ecommerce, Data Analyst
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below

Landmark Digital

Meet Landmark Digital – we’re part of the Landmark Group, one of the largest retail and hospitality organisations in the Middle East, North Africa and India. We’re guardians of the group’s digital arm which encompasses Enterprise and E-commerce Tech, Product Management, User Design, Omni Operations, Customer Experience, Loyalty, Content Production, Studio, Growth and Mar Tech, Finance and HR functions. With a futuristic outlook we strive to make the digital experience of our customers seamless.

Agile

Work Culture

Within the digital function, you’ll be hands‑on from day one, working in squads to make independent decisions and game‑changing contributions that directly impact millions of customers. You’ll collaborate every day with teammates from 20+ nationalities, across Dubai, India, Europe and the US.

Space for Excellence

Landmark Digital has a dedicated and growing software development centre in Bangalore, India, where we incubate, design and optimise our products and experiences. We also offer the option to work remotely for certain key roles.

New Technologies to Play With

You’ll work with the latest in Enterprise and E-commerce tech, headless commerce, open source, microservices, Java Spring Boot and Spring Cloud, React Native iOS and Android apps, React frontend and a host of the latest cloud‑native technologies hosted on Azure Cloud.

Focus on Learning & Growth

Excellent remuneration and perks are part of the package, but we also budget ample time and resources for training and upskilling.

Fun at Work

You’ll enjoy our well‑equipped breakrooms (FIFA and pool are huge favourites), team events, celebrations and a host of other amenities.

Job Purpose

To drive the Fashion e‑commerce business through data‑led insights that improve customer journey, category performance, and conversion rates. The role focuses on decoding how customers browse, engage, and purchase across the fashion ecosystem — from new arrivals to checkout — to build a seamless and personalized experience that fuels growth.

Job Description

The Product Analyst – Fashion will act as a key business partner for the home division. You will assess navigation and discovery paths, filter and sort performance, and visual merchandising efficiency to inform strategic decisions for category growth. Your insights will guide roadmap planning, UX enhancements, and assortment prioritisation.

Key Responsibilities
  • Analyze end‑to‑end customer journeys for fashion categories across web and app.
  • Identify conversion gaps in category pages, PDPs, and checkout flows; propose optimisation experiments.
  • Partner with Product Managers and Business teams to design metrics for new features (filters, recommendations, etc.).
  • Build and automate dashboards to track KPIs like traffic, add‑to‑cart rate, and sell‑through.
  • Perform A/B testing and derive insights to drive higher CTRs and conversions.
  • Collaborate with UX and marketing to align personalisation, visual hierarchy, and content strategies.
  • Present findings to senior stakeholders through clear data storytelling.
  • Strong understanding of fashion e‑commerce trends, funnel metrics, and category merchandising.
  • Skilled in consumer behaviour analytics, segmentation, and competitor benchmarking.
  • Comfort with large datasets, hypothesis testing, and growth experimentation.
Knowledge, Skills & Experience

Job Experience

  • 4–7 years in product or e‑commerce analytics, preferably in fashion, apparel, or lifestyle domains.
  • Demonstrated impact on revenue or conversion improvement through insights.
  • Experience in working cross‑functionally with design, product, and category teams.
Required Skills
  • Funnel analysis & optimisation
  • Category/assortment analytics
  • Clickstream & heatmap analysis
  • Cohort and behavioural segmentation
  • Strong collaboration & data storytelling
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