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Tier-1 brand, metro location, mid-level ML role, and generalist data science skills increase competition.
Core ML skills transfer across industries but sales-forecasting domain knowledge raises medium domain specificity.
Explicit minimum experience plus end-to-end ML and deployment requirements create moderately strict filters.
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Design, build, and deploy scalable demand forecasting models (time-series, ML-based) to predict product demand across SKU, category, channel, and regional levels.
Own the end-to-end ML lifecycle including data exploration, feature engineering, model training, validation, deployment, monitoring, and iteration.
Develop and optimize discount and price simulation tools to support margin maximization and strategic pricing decisions.
Bachelor's or Master's Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.
Minimum 3 years of experience in Data Analytics, Data Science, Data Mining, Artificial Intelligence, or related areas with a Bachelor's degree.
Full-time onsite presence required at company facilities (office-based with at least 3 days/week onsite).
Experience with statistical programming, machine learning engineering fundamentals, and data quality management is implied but not strictly specified as mandatory.
Experienced in handling complex, high-dimensional data problems with strong skills in innovative solution development and advanced analytical modeling.
Proficient with managing full ML lifecycle and operationalizing data science solutions at scale in collaboration with cross-functional teams.
Able to present complex data-driven insights to senior stakeholders and drive business impact through strategic recommendation.