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Tier-1 brand, mid-level ML role, metro location, broad skills increase competition.
Core ML and forecasting skills transfer across industries, but sales-domain knowledge increases sector specificity.
Explicit six-year requirement and domain-specific ML deployment experience make filters stringent.
Design, build, and deploy scalable demand forecasting models at SKU, category, channel, and regional levels using time-series and ML techniques.
Develop and operate discount and price simulation tools to optimize discount strategies and maximize margin.
Own the end-to-end ML lifecycle including data exploration, feature engineering, model training, validation, deployment, monitoring, and continuous improvement.
Bachelor's or Master's degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics, or equivalent.
Minimum 6 years of relevant experience in Data Analytics, Data Science, Data Mining, Artificial Intelligence, Pattern Recognition, or equivalent.
Strong expertise in statistical methods, machine learning engineering fundamentals, and data quality management.
This is an onsite role requiring full-time presence at company facilities with office-based team members working in-person at least 3 days per week.
Experienced in handling multifaceted, high-dimensional data and developing innovative, validated analytical models independently.
Capable of maintaining scalable data pipelines and integrating data science solutions with enterprise systems across cross-functional teams.
Proficient in translating complex data insights into strategic recommendations for senior stakeholders to influence business decisions.