• In-depth understanding of the retail sector, including consumer behavior, supply chain dynamics, inventory management, demand planning and forecasting and industry trends
• Proficiency in analyzing large datasets related to retail operations, customer transactions, and market trends to extract actionable insights for clients
• Experience in developing demand forecasting models, optimizing inventory management strategies
• Proficiency in statistical methods and forecasting algorithms , using both time – series based and machine learning and deep learning based methods for analyzing data sets
• Strong understanding and hands-on experience with machine learning and deep learning algorithms and techniques such as supervised and unsupervised learning, classification, clustering, and anomaly detection
• Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases
• Proficient in working with relational databases (e.g., SQL) and NoSQL databases
• Experience with data warehousing and data lakes
• Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow, Pytorch, MLlib)
• Advanced level programming in SQL or Python/Pyspark
• Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc.