Key Responsibilities:

• Work on data collection, cleaning, and preprocessing
• Perform exploratory data analysis (EDA) to identify patterns and trends
• Build, train, and evaluate predictive models (regression, classification, forecasting)
• Support data modeling activities including feature engineering and model optimization
• Assist in deploying or integrating basic ML/AI models into applications or workflows
• Work with Python, SQL, and libraries like Pandas, NumPy, Scikit-learn
• Prepare dashboards, reports, and insights for business decision-making
• Collaborate with cross-functional teams to solve data-driven problems

Required Skills:

• Strong basics in Python and SQL
• Understanding of statistics and machine learning concepts
• Knowledge of predictive modeling techniques
• Familiarity with data visualization tools (optional but good to have)
• Analytical thinking and problem-solving ability

Good to Have:

• Exposure to time-series forecasting, NLP, or deep learning
• Experience with model evaluation metrics (accuracy, precision, recall, RMSE)
• Academic or personal projects in ML/AI or prediction models