Staff Product Manager, Monetization (AI-Native)
2 мес. назад
ChinaWorldwideLeadOnsite
Senior independent contributor defining and shipping AI-native data product strategy to generate new revenue streams.
О компании
- Our Journey The 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, 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, 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, continues to create value for both members and
Другое
- Data-Driven Advertising: Explore and define how 's purchase signals can power more measurable, high-impact advertising experiences for merchants and brands
- New Revenue Surfaces: Identify and validate how '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 's data to build smarter audience segments, predictive signals, and automated ad optimisation tools
- Monetization Architecture: Define how '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
- 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