Product Research & Planning: Contribute to market and customer needs research to help shape product vision and roadmap. Assist in maintaining the product backlog, planning features and refining priorities with the team. 

Data Analysis & Quality Improvements: Define metrics (coverage, quality, cost) to identify improvement opportunities. Support initiatives to optimise product quality and efficiency (making data production cheaper while keeping quality high). 

Customer Requirements & Feedback: Gather and organise customer requirements, use cases and feedback (from internal and external stakeholders). Help translate these insights into clear feature ideas or bug fixes for the engineering and map operations teams. 

Cross-Team Collaboration: Work closely with engineering, sourcing, map operations, map expert teams to ensure requirements are understood and implemented correctly. Assist in day-to-day product execution, including tracking progress, triaging incoming requests (e.g. urgent quality issues in specific regions), and coordinating on timely data deliveries. 

Stakeholder Communication: Support the communication of product updates and results to stakeholders. Help prepare simple reports and presentations using meaningful metrics to explain “why” certain improvements or features are needed and how success is measured. 

Geospatial Product Fundamentals: How core map data (like administrative areas and postal polygons) is managed in a live map data pipeline and how it underpins search accuracy, geocoding precision, and map visualisations at global scale. 

Product/Engineering Collaboration: Practical experience in a cross-functional environment, working with developers, map operations and data analytics teams to bring product improvements from idea to implementation.  

Customer-Centric Product Management: Hands-on insight into gathering customer feedback and translating it into actionable product changes, learning to balance customer value with technical feasibility and cost. 

Real-World PM Skills: Experience with key PM activities such as backlog grooming, prioritisation trade-offs, stakeholder reporting, and adapting to new opportunities or issues as they arise in a complex data product. 

Applying AI in product management: Learn how to leverage modern AI tools to enhance product management work— including supporting research, data analysis, as well as automating repetitive tasks such as documentation, reporting, and backlog preparation to improve efficiency and focus on higher-impact work. 

Education: You are currently pursuing a Bachelor’s or Master’s degree in a relevant field (e.g. Computer Science, Data Science, Geoinformatics, or Business). 

Analytical Skills: Strong analytical and problem-solving mindset. Comfortable working with data and metrics  to derive insights. 

Communication: Good communication skills in English, both written and verbal. Able to collaborate well in a team environment and clearly convey findings or ideas. 

Proactive Learner: A self-motivated, curious learner who is not afraid to ask questions or dive into new technical domains. Enthusiasm for solving real-world problems through technology. 

Geospatial Knowledge: Familiarity with GIS tools or geospatial concepts (maps, coordinates, geo-analytics) is a plus, as our product is inherently geo-based). 

Data Tools: Basic experience with data analysis tools (SQL, Python, etc.) for working with datasets or visualising data insights. 

Product Management Basics: Understanding of agile methodologies or prior experience in a project or product role (e.g. school projects, hackathons) can be an advantage.