Our Journey
The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 60 million shoppers across 13 markets. In 2025, the Group continued its global growth with its expansion into North America. Driven by the vision to make every day more rewarding, ShopBack is dedicated to saving members money and time, and delivering delight every day. The platform also enables merchants and brands to engage with their members in a cost-effective manner. Founded in 2014, ShopBack now powers over US$5.5 billion in annual sales for over 20,000 online and in-store partners, and has rewarded shoppers with more than US$800 million (over S$1 billion) in Cashback to date. Through its innovative offerings, ShopBack continues to create value for both members and merchants. Notably, its payment solution, ShopBack Pay, offers members a convenient and rewarding payment option at checkout.
Your Role
As an AI-Native Staff Product Manager, you will define and ship ShopBack's data product strategy — packaging our proprietary data into high-value products that generate new revenue streams. You will operate as a senior independent contributor reporting directly to the CPO, working across Data, Ads, and Merchant teams to bring these products to life.
This is a zero-to-one role. You will be the dedicated PM on this problem.
What You'll Own
Data-Driven Advertising: Explore and define how ShopBack's purchase signals can power more measurable, high-impact advertising experiences for merchants and brands
New Revenue Surfaces: Identify and validate how ShopBack's first-party data can be packaged into products that unlock value for external partners — without compromising user trust or data control
AI-Driven Enhancements: Layer AI on top of ShopBack's data to build smarter audience segments, predictive signals, and automated ad optimisation tools
Monetization Architecture: Define how ShopBack's data assets are productised, priced, and distributed — without ever compromising user trust or data control
Go-to-Market: Work closely with merchant sales and partnerships teams to commercialise data products and close deals
Discovery: Spend time with merchants, advertisers, and enterprise buyers to understand their measurement and targeting pain points before you build
Essentials to Succeed
Data Product Fluency: You've built or monetized data products before — audiences, segments, attribution models, or alternative data feeds — and understand how buyers evaluate and pay for them
Retail Media Instinct: You understand how closed-loop advertising works and why purchase data is the most defensible ad-targeting signal available
AI-Native Thinking: You know when to apply LLMs, ML models, or simple heuristics to a data problem — and you default to what ships fastest with the most impact
Commercial Acumen: You think in revenue models, not just features. You understand the difference between licensing, SaaS, and usage-based data pricing
Stakeholder Influence: You move cross-functional teams without direct authority — data engineering, legal, sales, and growth all need to be in your orbit
High Ownership: You find the data you need, define the problem yourself, and ship without waiting for perfect conditions
Impact First: You measure success in GMV uplift, revenue unlocked, and advertiser retention — not roadmap velocity