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Strong global brand and remote role increase interest, while senior specialization moderates applicant density.
Requires deep forecasting and supply-chain domain expertise, reducing cross-industry transferability.
Mandatory 10+ years, forecasting and Databricks expertise create strict screening filters.
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Lead and refine advanced statistical forecasting models for demand forecasting to improve forecast accuracy and reduce bias.
Perform root cause and trend analysis on large datasets and produce actionable insights and visualizations using tools such as Python, PySpark, SQL, and Power BI/Tableau.
Develop, deploy and maintain predictive algorithms on platforms like Databricks, collaborating closely with demand planners to enhance model explainability and performance.
Bachelor's degree required; Master’s preferred in quantitative fields such as Statistics, Applied Mathematics, or Engineering.
10+ years of experience in statistical modeling, machine learning, and forecasting with domain focus on supply chain and demand planning.
Proficient in Python and PySpark, experience with Databricks or similar data science cloud platforms.
Experience leading multiple projects in supply chain and forecasting within large, complex businesses; knowledge of FMCG/Retail/Food & Beverage data is a plus.
Senior-level analytic expert with extensive experience in supply chain forecasting and demand planning in complex business environments.
Hands-on with Python/PySpark coding and deploying statistical and machine learning models on cloud platforms such as Databricks.
Capable of translating complex data science outcomes into clear business insights and managing cross-functional coordination for project execution and continuous model improvement.