Spares Forecasting Manager

Dyson

Singapore, Singapore
Spares demand forecasting
Data-driven forecasting process
Statistical and machine-learning models
Lead Spares Demand Forecasting by transitioning the function from manual methods to a robust, data-driven process using best-in-class analytics and technology

Job Summary

  • Lead Spares Demand Forecasting by transitioning the function from manual methods to a robust, data-driven process using best-in-class analytics and technology.
  • Own and Optimise Data Models by overseeing statistical and machine-learning models, adjusting parameters in response to shifting demand signals, new product introductions, and business priorities.
  • Achieve Forecast Accuracy by setting and tracking KPIs, rapidly analysing deviations, correcting root causes, updating models, and communicating learnings.

Matching Summary

Lead Spares Demand Forecasting by transitioning the function from manual methods to a robust, data-driven process using best-in-class analytics and technology.

Skills & Requirements

Must-have

  • Spares demand forecasting
  • Data-driven forecasting process
  • Statistical and machine-learning models
  • Global forecasting model deployment
  • Forecast accuracy KPIs
  • Cross-functional collaboration

Nice-to-have

  • Customer satisfaction focus
  • Continuous improvement mindset
  • Data-led evolution
  • Globally aligned and locally agile

Key Requirements

  • Experience managing demand forecasting, planning, or analytics in a global business
  • Strong grasp of forecasting & data tools
  • Track record of shifting functions from manual to automated/data-driven
  • Technical literacy in statistical or machine-learning models

Work Rights

Not specified

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