Key Responsibilities
Understand business problems and translate them into analytical solutions.
Collect, clean, transform, and prepare structured and unstructured datasets.
Perform exploratory data analysis and feature engineering.
Build and deploy machine learning models for prediction, classification, clustering, recommendation, and optimization.
Train, evaluate, and fine-tune models using appropriate performance metrics.
Develop predictive and prescriptive analytics solutions to improve business outcomes.
Work on customer segmentation, forecasting, churn prediction, propensity modeling, and other advanced analytics use cases.
Collaborate with Data Engineers and business stakeholders for model deployment and operationalization.
Present insights and recommendations to business teams and clients.




Ensure model governance, monitoring, and continuous improvement.

Must-Have Qualifications
Bachelor's/Master's degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
3+ years of hands-on Data Science experience.
Robust proficiency in Python and SQL.
Experience with Machine Learning algorithms:
Regression
Classification
Clustering
Ensemble Methods (XGBoost, Random Forest)
Time Series Forecasting
Solid understanding of Statistics, Hypothesis Testing, Probability, and Experimental Design.
Experience working with large datasets.

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