Specialist, Material Planning-SIOP

Carrier — Capital Cyberscape, 2nd Floor, Ullahwas, Sector 59, Gurugram, Haryana 122102

Role : Specialist, Material Planning-SIOP Location : Gurugram Full/ Part-time : Full Time About Carrier Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating innovations that bring comfort, safety and sustainability to life. Through cutting-edge advancements in climate solutions such as temperature control, air quality and transportation, we improve lives, empower critical industries and ensure safe transport of food, life-saving medicines and more. Since inventing modern air conditioning in 1902, we lead with purpose: enhancing the lives we live and the world we share. We continue to lead because of our world-class, inclusive workforce that puts the customer at the center of everything we do. For more information, visit corporate.carrier.com or follow Carrier on social media at @Carrier. About the role 9-10 year’s experience as a data scientist Experience with sales/inventory/operations data, planning data, data modeling, AI-Powered Demand Insights, Agentic AI for Supply Chain Actions, AI Skills & Recommendations, Email/Slack/Chat Integration for AI, Natural Language Query & Reporting. Discovery of data points, regression models, KPIs, building models, understand market data Develop and implement statistical forecasting models to predict future market demand, sales trends, and customer behavior. Utilize regression analysis techniques to understand the relationships between various factors and business outcomes. Collect, clean, and transform large datasets from various sources, including internal databases, external APIs, and public data repositories. Engineer relevant features from raw data to improve model performance and extract meaningful insights. Develop and implement data pipelines for efficient data extraction, transformation, and loading (ETL). Develop and deploy machine learning models, including supervised and unsupervised learning algorithms (e.g., decision trees, random forests, support vecto

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