About this role
• Data Analysis: Proficient in data manipulation, cleaning, exploration, and visualization using tools like Python (pandas, numpy, matplotlib, seaborn) or Tableau.
• Machine Learning Modeling: Strong understanding and practical experience with various ML algorithms, particularly time series analysis techniques (ARIMA, Prophet, LSTM, etc.).
• Feature Engineering: Ability to identify, create, and select relevant features to improve model accuracy and interpretability.
• Large-Scale Time Series Experience: Preferred experience working with large time series datasets, including data management and efficient processing techniques.
• Programming Proficiency: Strong programming skills in Python, including experience with relevant libraries for data science and machine learning.
• Statistical Knowledge: Solid foundation in statistical concepts, including hypothesis testing, regression analysis, and time series analysis.