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Well-known unicorn, metro location, and mid-level ML role with forecasting specialization yields medium competition.
Requires domain-specific supply-chain demand forecasting expertise, limiting cross-industry transferability.
Explicit 6+ years plus mandatory time-series forecasting and supply-chain experience makes shortlisting strict (high).
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Develop and optimize advanced demand forecasting and planning models using machine learning and statistical techniques such as time series, regression, and heuristics.
Apply and customize models for demand sensing, anomaly detection, simulation, and market intelligence to improve supply chain decision-making.
Collaborate with clients and cross-functional teams to ensure successful delivery and real-time integration of AI-driven supply chain solutions.
6+ years of experience specifically in large-scale time series forecasting using heuristic hierarchical best-fit models and algorithms like exponential smoothing, ARIMA, Prophet.
Bachelor's degree in Computer Science, Mathematics, Statistics, Economics, Engineering, or related field.
Proficient in Python and/or R with deep knowledge of statistical and machine learning algorithms, feature engineering, tuning, and testing.
Strong background in applied analytics within supply chain domains such as demand planning, supply planning, and market intelligence.
Experienced in building scalable machine learning frameworks for enterprise supply chain applications with an emphasis on statistical rigor.
Able to independently analyze complex problems, synthesize data, and communicate technical results clearly to diverse stakeholders.
Familiar with integration of machine learning models into production environments and collaborative project delivery with clients and multi-disciplinary teams.