Machine Learning Product Manager

This is a fully remote position, open to applicants in Austria.

📋 Description

• Take ownership of the product vision, strategy, and roadmap for refurbed’s AI-driven steering functionalities.

• Convert the company and product vision into well-defined product challenges, business needs, decision areas, user stories, and quantifiable success metrics.

• Collaborate closely with teams to establish how ML models and decision-making systems can enhance marketplace expansion.

• Identify and prioritize the most impactful use cases for intelligent steering.

• Collaborate with Data Science and Engineering to outline essential data inputs and model specifications.

• Lead investigations into existing commercial processes and decision-making logic.

• Create product mechanisms for human-in-the-loop control.

• Employ experimentation to validate recommendations.

• Define and monitor product KPIs and metrics related to model impact.

• Articulate complex ML and optimization ideas clearly to stakeholders.

⛳️ Requirements

• Over 5 years of experience in product management, including several years in ML, AI, or algorithmic decision-making.

• Proven ability to collaborate with Data Science and Engineering teams on ML-driven products, including converting business challenges into model objectives, product specifications, and measurable results.

• Experience with marketplace dynamics, pricing systems, recommendation engines, ad tech, and ranking is highly desirable.

• Outstanding analytical skills and a solid understanding of experimentation.

• Ability to navigate complex commercial trade-offs.

• Strong technical proficiency.

• Experience in working with ambiguous, cross-functional, and highly strategic product domains.

• Excellent stakeholder management abilities.

• A structured, results-oriented approach to product discovery and delivery.

• Exceptional communication skills.

• A passion for sustainability, marketplaces, AI, and the development of intelligent systems.

🏝️ Benefits

• Dedicated learning budget.

• Private sessions with experts for personal development and mental well-being.

• Internal workshops aimed at skill enhancement and collaboration.