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Mid-level, metro ML/data scientist role with broad skills at a recognizable brand increases competition.
Role focuses on demand-forecasting and retailer-specific factors, reducing cross-industry transferability.
Explicit 5+ years requirement, master's degree, and mandatory ML/time-series, SQL and cloud skills raise filtering strictness.
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Develop and deploy advanced time-series and machine learning models for demand forecasting across multiple brands.
Collaborate with business and cross-functional teams to identify prediction opportunities and provide modeling updates to leadership.
Conduct data analysis, feature engineering, and model evaluation to improve forecasting accuracy and operational efficiency.
Master's degree in Computer Science, Statistics, Mathematics, or related field.
5+ years of experience in predictive modeling, time-series analysis, machine learning, and statistical modeling.
Experience specifically in building demand forecast models.
Proficiency in Python, R, SQL, and familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Experienced in operating within fast-paced, collaborative environments delivering production-grade ML models.
Strong background in demand forecasting and handling shipment demand influencing factors.
Able to communicate complex analytical results effectively to both technical and business stakeholders.