Programming Language: Python
Database Knowledge: SQL/NoSQL
Machine Learning and Statistical Analysis
Machine - Learning Algorithms: Understand common ML algorithms like linear/logistic regression, decision trees, random forests, SVMs, and neural networks. Pick the right one for sales forecasting and demand analysis.
Time - Series Analysis: Be familiar with ARIMA, SARIMA, Prophet for time - series sales data modeling and forecasting.
Statistical Methods: Have a good stats base. Know about probability, hypothesis testing, regression, and clustering for data exploration and model work.
Big Data Technologies
Hadoop Ecosystem: Understand Hadoop parts like HDFS, MapReduce, Hive, Spark to process large - scale retail data.
Cloud Computing Platforms: Be familiar with cloud services like Ali Clound, AWS, GCP, Azure, for data storage, computing, and model deployment.
Previous working experience in Sales & Operations Planning (S&OP) related solution development in retail (FMCG) field is preferred but not mandatory.
Work Experience
Programming Language: Python
Database Knowledge: SQL/NoSQL
Machine Learning and Statistical Analysis