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Tier-1 brand, mid-level (6+ years) role in Bangalore increases candidate competition.
Specialized supply-chain demand-forecasting and time-series expertise reduces cross-industry transferability.
Explicit 6+ years plus domain-specific time-series and supply-chain forecasting requirements make filters strict.
Develop and optimize advanced machine learning models for demand sensing, forecasting, anomaly detection, and optimization within retail supply chains.
Apply statistical and AI/ML techniques including time series forecasting algorithms (exponential smoothing, ARIMA, prophet) and heuristic optimization methods at scale.
Collaborate with cross-functional teams and clients to ensure successful delivery and real-time integration of forecasting and planning solutions.
6+ years of experience in large-scale time series forecasting using heuristic-based hierarchical best-fit models and algorithms like exponential smoothing, ARIMA, and prophet.
Bachelor's degree in Computer Science, Mathematics, Statistics, Economics, Engineering, or related statistical background.
Proficiency in Python and/or R for Data Science and deep knowledge of statistical and machine learning algorithms, feature engineering, and scalable ML frameworks.
Experience in supply chain and planning domains such as demand planning, supply planning, market intelligence, pricing, and inventory optimization.
Experienced in applied analytics specifically within supply chain planning and demand forecasting environments.
Capable of independent analytical problem solving with strong communication and presentation skills for client-facing and collaborative contexts.
Comfortable operating within cross-functional teams in a high-growth, AI-driven technology environment delivering complex forecasting products.