Data Scientist - Demand Forecasting
Core Responsibilities We are seeking a skilled Data Scientist with hands-on forecasting expertise to join our Demand Forecasting team. This role requires strong technical capability in time series and machine learning models, combined with the ability to translate data insights into clear business narratives that drive decision-making. You will spend approximately 50% of your time on operational forecast delivery and 50% on improving accuracy, analysing results, and innovating.
Play your part in our team succeeding:
- Deliver operational forecasts: Contribute to the continuous production and monitoring of forecasts used by LEGO demand planners worldwide, ensuring stability and reliability in operations.
- Improve forecasting models: Design, test and implement enhancements to time series and ML models, including in-depth understanding of algorithm fundamentals and parameters, to increase accuracy and adoption.
- Engage with collaborators: Partner with demand planners and other business collaborators to increase forecast adoption and enable data-driven decision-making.
- Analyse and interpret forecast performance: Identify patterns in data, evaluate results, and provide clear narratives on drivers, outcomes, and business implications.
- Bridge business and data science: Act as a translator between technical outputs and business needs, ensuring partners understand and trust forecasts.
- Contribute to scalable solutions: Support the development and deployment of forecasting workflows in production within Databricks.
- Minimum 3 years of experience in forecasting, with direct application of time series and ML models.
- Proficiency in Python, SQL, and Databricks
- Demonstrated ability to translate technical analyses into business-relevant insights through clear communication and data storytelling.
- Experience balancing continuous operational delivery with model innovation and improvement.
- Strong analytical outlook with attention to detail and data quality.
- Background in supply chain, retail, planning or other forecasting environments.
- Experience with MLOps practices and scalable model deployment.
- Experience with Pyspark
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