Staff Product Manager, Monetization (AI-Native)

Our Journey

The ShopBack Group is Asia-Pacific's leading shopping and rewards platform, trusted by over 20 million active members across 13 markets, including Germany and the United States. Driven by the vision to make every day more rewarding, ShopBack saves members money and time with more ways to earn and more to do with what they earn, and empowers merchants and brand partners to effectively engage its members. Founded in Singapore in 2014, ShopBack now powers over US$5.5 billion in annual sales and half a million transactions a day for more than 20,000 online and in-store partners.

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

ShopBacker Traits

• Agency - We take ownership and act, rather than waiting for permission. When something's blocking progress, we find a way through it and follow through until it's done.
• Judgement - We aim for high-impact decisions, not just easy wins, and we put the bigger picture ahead of individual interests. That means moving quickly and confidently, while staying thoughtful about when a call really matters.
• Learning Velocity - We pick up new skills fast and let go of old habits just as quickly when something better comes along. We benchmark ourselves against the best and keep raising our own bar.
• Tenacity - We stay in it when things get hard, keeping a level head under pressure. We debate openly before deciding, then commit fully — and support each other along the way.

What's in it for ShopBackers

• Career growth opportunities to take on greater challenges that help you realise your ambitions.
• Be part of a winning team on a journey to global scale.
• Competitive compensation based on performance.
• Candid, open, and collaborative culture where feedback is valued.