Machine Learning Product Manager
New
R
refurbedRefurbished Marketplace
This role is open to candidates based in Europe (including UK) only with a valid right to work. Source API remote eligibility restrictions: Germany, United Kingdom, United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 5+ years of product management experience, with a few years in ML, AI or algorithmic decisioning.
- Required Skills
- Artificial IntelligenceMachine LearningProduct ManagementData scienceStakeholder management
Requirements
- 5+ years of product management experience, with a few years specifically in ML, AI, or algorithmic decisioning.
- Strong ability to collaborate with Data Science and Engineering teams on ML-powered products.
- Experience translating business problems into model objectives, product requirements, and measurable outcomes.
- Strong analytical skills with a solid understanding of experimentation.
- Technical fluency to discuss data pipelines, model inputs and outputs, and system constraints.
- Ability to reason through complex commercial trade-offs.
- Experience in highly strategic, ambiguous, and cross-functional product areas.
- Strong stakeholder management skills to align teams with varying goals and incentives.
- Structured, outcome-oriented approach to product discovery and delivery.
- Excellent communication skills for explaining complex systems to diverse stakeholders.
- Experience with marketplace dynamics, pricing, recommendations, or ad tech is a strong plus.
Responsibilities
- Own the product vision, strategy, and roadmap for refurbed’s AI-powered steering capabilities.
- Translate company vision into clear product problems, business requirements, and measurable success criteria.
- Partner with Data Science, Engineering, and Commercial teams to define ML model requirements and decisioning systems.
- Identify and prioritize high-value use cases for intelligent steering.
- Work with cross-functional teams to define data inputs, model monitoring, and feedback loops.
- Lead discovery of commercial workflows to identify pain points and decision logic.
- Design product mechanisms for human-in-the-loop control.
- Validate recommendations through experimentation before scaling.
- Define and track product KPIs and model-impact metrics to ensure business outcomes.
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