
Required Qualifications:
- Bachelors or Masters degree in Computer Science, Statistics, Mathematics, Data Science, or related quantitative field, with experience in Retail domain projects as a mandate.
- 11-18 years of experience delivering ML models solving real-world business problems.
- Strong expertise in Python and ML libraries such as Scikit-learn, XGBoost, LightGBM, CatBoost, Statsmodels.
- Deep understanding of machine learning theory, feature engineering, sampling strategies, bias/variance trade-offs, and model diagnostics.
- Strong experience with analytical and statistical techniques: regression, hypothesis testing, ANOVA, time-series, clustering, survival models, probability distributions.
- Hands-on experience working with cloud platforms (AWS, GCP, or Azure).
- Solid understanding of data pipelines, data quality checks, and best practices for production-grade model development.
- Familiarity with ML engineering / MLOps workflows and tools (Airflow, MLflow, Docker, Kubernetes, CI/CD pipelines).
- Proficiency in SQL and experience with large-scale structured and unstructured datasets.
- Excellent communication skills and the ability to translate technical output into business impact.
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