Data Scientist

Role & responsibilities

• Analyze large and complex datasets to identify business insights and patterns.
• Develop, train, validate, and optimize machine learning models.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
• Build predictive and classification models using appropriate ML algorithms.
• Apply statistical techniques such as hypothesis testing, regression, probability analysis, and experimentation.
• Develop solutions using Python, SQL, Pandas, NumPy, and Scikit-learn.
• Work on supervised and unsupervised learning techniques.
• Evaluate models using suitable metrics such as precision, recall, F1-score, ROC-AUC, RMSE, and MAE.
• Collaborate with Data Engineers, ML Engineers, business analysts, and stakeholders.
• Deploy and monitor ML models in production environments.
• Communicate technical findings and recommendations to business stakeholders.
• Follow model governance, versioning, documentation, and reproducibility practices.