1 day ago

Lead - Supply Chain Decision Intelligence & Operations Research

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Apply mathematical rigor to optimize and simulate decisions across On’s global supply chain. Develop optimization, simulation, and scenario models for inventory, capacity, fulfillment, demand/supply balancing, service risk, and lifecycle planning. Build rapid prototypes and model-ready datasets using Python, SQL, and other analytical tools, then partner with technology teams to transfer validated solutions into scalable production systems.

Location: Zurich

Employment Type: Full time

Job Function: Supply Chain & Logistics

Seniority: Mid level

Key Responsibilities

•Develop and test optimization, simulation, and scenario models for inventory, capacity, fulfillment, demand/supply balancing, service risk, and product lifecycle decisions.
•Build rapid prototypes with planners and business stakeholders before industrialisation.
•Prepare model-ready data by exploring, joining, transforming datasets, and documenting assumptions and validation rules.
•Partner with Technology teams (Data Engineering, Data Science, Optimization Engineering, and platform teams) to transfer prototypes into scalable solutions with clear model specifications and acceptance criteria.
•Enable scenario planning and translate model outputs into actionable recommendations and trade-offs for planners and senior leaders.

Key Requirements

•5 to 7 years of relevant experience in industry, consulting, applied research, academia, or a combination of these environments.
•Strong foundations in operations research, applied mathematics, industrial engineering, management science, decision science, systems engineering, statistics, physics, or a similar quantitative discipline.
•Strong experience in optimization, simulation, stochastic processes, probabilistic modelling, or related quantitative methods.
•Proficiency in Python, R, Julia, MATLAB, or an equivalent environment, and strong SQL/data-wrangling skills.
•Ability to formulate real-world problems mathematically and implement computational models from complex, imperfect data.

Experience:5-7 yearsSupply chainLogisticsRetailManufacturingOperations researchStochastic optimizationApplied researchConsulting

Skills:Problem-framingAnalytical thinkingIndependent workExplainabilityCollaboration

Languages:English

Tech Stack:PythonSQLHexRJuliaMATLABGurobiCPLEXPyomoPuLPOR-ToolsJuMPSciPyAI-assisted codingAgentic workflowsGenerative tools

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: 4.0

Website LinkedIn

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On Holding

1 day ago

Lead - Supply Chain Decision Intelligence & Operations Research

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: Zurich

Employment Type: Full time

Job Function: Supply Chain & Logistics

Seniority: Mid level

Key Responsibilities

•Develop and test optimization, simulation, and scenario models for inventory, capacity, fulfillment, demand/supply balancing, service risk, and product lifecycle decisions.
•Build rapid prototypes with planners and business stakeholders before industrialisation.
•Prepare model-ready data by exploring, joining, transforming datasets, and documenting assumptions and validation rules.
•Partner with Technology teams (Data Engineering, Data Science, Optimization Engineering, and platform teams) to transfer prototypes into scalable solutions with clear model specifications and acceptance criteria.
•Enable scenario planning and translate model outputs into actionable recommendations and trade-offs for planners and senior leaders.

Key Requirements

•5 to 7 years of relevant experience in industry, consulting, applied research, academia, or a combination of these environments.
•Strong foundations in operations research, applied mathematics, industrial engineering, management science, decision science, systems engineering, statistics, physics, or a similar quantitative discipline.
•Strong experience in optimization, simulation, stochastic processes, probabilistic modelling, or related quantitative methods.
•Proficiency in Python, R, Julia, MATLAB, or an equivalent environment, and strong SQL/data-wrangling skills.
•Ability to formulate real-world problems mathematically and implement computational models from complex, imperfect data.

Experience:5-7 yearsSupply chainLogisticsRetailManufacturingOperations researchStochastic optimizationApplied researchConsulting

Skills:Problem-framingAnalytical thinkingIndependent workExplainabilityCollaboration

Languages:English

Tech Stack:PythonSQLHexRJuliaMATLABGurobiCPLEXPyomoPuLPOR-ToolsJuMPSciPyAI-assisted codingAgentic workflowsGenerative tools

Company Brief

On Holding

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: 4.0

Website LinkedIn