Senior Product Manager - Inventory Optimization & ML Allocation

On Holding
Zurich, London
Workplace: OnsiteFull timeFunction: Product ManagementSkills: ["Cross-functional leadership","Product mindset","Experimentation","Measurable impact","Trust in algorithmic decisions"]

Own the Inventory Visibility Service and the evolution of allocation from heuristic rules to ML-driven forecasting. Stabilize and optimize real-time inventory counts, build predictive initial placement models, and design ML optimization engines that improve channel inventory profitability. Partner with Supply Chain Operations to deploy autonomous, real-time AI agents that ingest external signals and autonomously rebalance stock—while integrating event-driven systems across Dynamics 365, OMS, and the Supply Chain Control Tower.

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FursaFursa
On Holding
On Holding
1 day ago

Senior Product Manager - Inventory Optimization & ML Allocation

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Last checked: 16 hours agoStatus: Live

Job Summary

Own the Inventory Visibility Service and the evolution of allocation from heuristic rules to ML-driven forecasting. Stabilize and optimize real-time inventory counts, build predictive initial placement models, and design ML optimization engines that improve channel inventory profitability. Partner with Supply Chain Operations to deploy autonomous, real-time AI agents that ingest external signals and autonomously rebalance stock—while integrating event-driven systems across Dynamics 365, OMS, and the Supply Chain Control Tower.
Location: Zurich, London
Workplace: Onsite
Employment Type: Full time · Permanent
Job Function: Product Management
Seniority: Mid level

Key Responsibilities

  • •Own inventory visibility strategy and reliability, ensuring accurate, sub-second inventory counts across the global supply chain network.
  • •Stabilize the existing heuristic allocation engine by identifying bottlenecks, patching critical logic gaps, and ensuring reliable daily operations.
  • •Partner with Supply Chain Operations to transition from legacy manual rule sets to continuous ML forecasting with strong stakeholder trust.
  • •Design and guide ML optimization engines to determine the most profitable inventory distribution across core channels, co-developing modern architecture with Data & AI.
  • •Define initial allocation strategies and deploy real-time AI agents that ingest news/market sentiment to trigger autonomous stock rebalancing workflows and integrate via event-driven APIs.

Key Requirements

  • •8+ years of technical product management experience across supply chain optimization (inventory visibility/OMS) and ML/data science product development.
  • •Proven track record stabilizing legacy heuristic rule engines and transitioning operations to algorithmic, ML-driven models.
  • •Literacy in optimization and forecasting, including probabilistic forecasting, linear programming, or financial risk modeling (e.g., cost of deviation).
  • •Strong AI application experience, including deploying autonomous agents and orchestrating automated decision workflows using unstructured external data.
  • •Ability to lead cross-functional science and engineering teams with a product mindset focused on experimentation and measurable business impact.
Experience:Supply chain optimizationMachine learningData scienceInventory visibilityOMS
Skills:Cross-functional leadershipProduct mindsetExperimentationMeasurable impactTrust in algorithmic decisions
Languages:English
Tech Stack:Microsoft Dynamics 365OMSSupply Chain Control TowerEvent-driven APIsInventory visibility serviceIVS

Company Brief

On Holding
Designs, manufactures, and sells performance running shoes, apparel, and accessories under the On brand. Combines Swiss engineering and innovation with lifestyle design to serve runners and athletes globally through retail and direct-to-consumer channels.
Industry: Fashion & Apparel
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Zurich, Switzerland
Founded: 2010
Glassdoor
Glassdoor: 4.0
WebsiteLinkedIn