Advanced AI-Driven Retail Merchandising Expert
Budget: $250 – $750 USD
Looking for a highly skilled Data Scientist with deep expertise in AI and Generative AI to lead cutting-edge retail merchandising and pricing analytics initiatives, driving scalable forecasting, optimization, and intelligent automation solutions.
-Leverage state-of-the-art AI and Generative AI techniques to drive innovation in retail merchandising and pricing analytics.
-Design, develop, and deploy advanced machine learning and optimization models to support data-driven business decisions.
-Build scalable solutions for demand forecasting, assortment optimization, price elasticity modeling, and inventory allocation and replenishment.
-Develop sophisticated demand forecasting systems using multivariate and hierarchical models for long-range, multi-echelon predictions.
-Address complex forecasting challenges such as cold-start problems, cross-level reconciliation, and scalability across large datasets.
-Design and implement AI/ML-driven assortment planning algorithms based on customer behavior and preference data.
-Apply advanced machine learning and deep learning techniques, including LSTM and Transformer-based models, to retail and e-commerce use cases.
-Utilize Large Language Models (LLMs), Generative AI, and agent-based systems to enhance analytics and automation capabilities.
-Implement optimization models to improve operational efficiency and maximize customer value.
Manage the full machine learning lifecycle, including model monitoring, retraining, experiment tracking, and performance evaluation.
-Develop and maintain CI/CD pipelines for reliable and scalable deployment of data science solutions.
-Work with modern machine learning frameworks and tools such as TensorFlow, PyTorch, OpenAI, and LangChain.
-Collaborate with cross-functional teams and integrate solutions with existing applications and data systems via APIs and web services.
-Leverage state-of-the-art AI and Generative AI techniques to drive innovation in retail merchandising and pricing analytics.
-Design, develop, and deploy advanced machine learning and optimization models to support data-driven business decisions.
-Build scalable solutions for demand forecasting, assortment optimization, price elasticity modeling, and inventory allocation and replenishment.
-Develop sophisticated demand forecasting systems using multivariate and hierarchical models for long-range, multi-echelon predictions.
-Address complex forecasting challenges such as cold-start problems, cross-level reconciliation, and scalability across large datasets.
-Design and implement AI/ML-driven assortment planning algorithms based on customer behavior and preference data.
-Apply advanced machine learning and deep learning techniques, including LSTM and Transformer-based models, to retail and e-commerce use cases.
-Utilize Large Language Models (LLMs), Generative AI, and agent-based systems to enhance analytics and automation capabilities.
-Implement optimization models to improve operational efficiency and maximize customer value.
Manage the full machine learning lifecycle, including model monitoring, retraining, experiment tracking, and performance evaluation.
-Develop and maintain CI/CD pipelines for reliable and scalable deployment of data science solutions.
-Work with modern machine learning frameworks and tools such as TensorFlow, PyTorch, OpenAI, and LangChain.
-Collaborate with cross-functional teams and integrate solutions with existing applications and data systems via APIs and web services.