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Oura is seeking a Forecast Analyst – Demand Planning to strengthen forecasting capabilities through better analytics, improved data integration, and scalable demand methodologies. This senior individual contributor role serves as the analytical engine behind demand planning, translating signals into accurate forecasts, building statistical baselines, and advancing the organization toward machine learning-enabled forecasting.
Key responsibilities include developing and operationalizing forecasting methodologies that improve accuracy and scalability across planning processes. You will build and refine statistical baseline forecasts incorporating historical demand, seasonality, promotions, product transitions, and channel mix. The role involves evaluating forecast performance through error diagnostics and bias analysis, then translating findings into actionable recommendations. You'll standardize forecasting logic and documentation to ensure transparency and repeatability.
Data integration is central to the position. You will partner with Data and Systems teams to improve the structure and reliability of demand planning inputs, connecting data across shipments, POS, inventory, promotions, and product lifecycle events. You'll identify opportunities to reduce manual work through better tooling and automation, and support business requirements for planning system enhancements.
Decision support is another core pillar. You will build scenario models, dashboards, and analytical tools to help the business understand demand risk and operational implications. Supporting monthly, quarterly, and long-range planning cycles, you'll create decision-ready analysis and translate complex findings into clear business narratives for both technical and non-technical stakeholders.
The ideal candidate has 6+ years in forecasting, demand planning, analytics, data science, or operations research. You must have strong experience building statistical forecasting methods in business environments, advanced SQL skills, and proficiency in Python, R, or similar analytical languages. Experience with large, messy datasets, model development and evaluation, and understanding of planning processes in consumer products, hardware, or retail is essential. Familiarity with demand planning tools, supply chain concepts, and machine learning approaches is highly valued.
