Writing clean, efficient, and well-documented Python code for automation, data processing, web scraping, API integrations, and backend scripting.
Building data pipelines using tools like Pandas, NumPy, and SQL to collect, clean, and transform raw data into meaningful formats.
Developing insightful reports and interactive dashboards using libraries like Matplotlib, Seaborn, Plotly, or Power BI integrations.
Performing statistical analysis and data visualization to identify trends, anomalies, and business opportunities.
Assisting with machine learning tasks such as data preprocessing, model training, and evaluation using frameworks like scikit-learn or TensorFlow (if applicable).
Collaborating effectively with teams, following best coding practices, and delivering on time.