Data Scientist

**JD:** Primary Skill set below – Traditional AI ML **Statistical \& Machine Learning** : Proficient in building **supervised learning models** (e.g., regression, classification, decision trees, ensemble methods). 1\. Skilled in **unsupervised learning** techniques (e.g., clustering, dimensionality reduction, anomaly detection). 2\. Ability to apply **statistical methods** for hypothesis testing, feature engineering, and model evaluation ( **ROC, AUC, precision\-** recall, etc.). 3\. **Programming \& Tools** : **Python, Jupyter Notebook** s, and libraries such as **scikit\-learn** , **pandas, NumPy** . **JD/Job Description/Responsibilities:** 1. Analyse large datasets and develop predictive models within Data Lake environments. 2. Write simple, efficient SQL queries and collaborate with data engineering teams to build and validate data pipelines with robust data checks. 3. Prepare, clean, and standardize data for analysis and modelling. 4. Build supervised and unsupervised ML models using Python and Jupyter Notebooks. 5. Communicate insights through clear reports and visualizations 6. Document processes and ensure data quality standards. 7. Stay updated on emerging technologies to improve model performance and reliability..