- Data Cleaning and Preparation.
- Data Analysis and Exploration.
- Statistical Analysis and Data Comprehension.
- Creating Data Visualizations.
- Creating Dashboards and/or Reports.
- Problem-Solving.
- A/B and Hypothesis testing.
- Building and Deploying Machine Learning Models.
- Tools and Languages used: Python (Numpy, Matplotlib, Pandas, Seaborn, OpenCV, Tensorflow/Keras, Pytorch, etc.), C/C++ (Eigen), MATLAB/SIMULINK.