Sr. Data Scientist

Role Descriptions: Hands-on experience on

1. Programming LanguagesStrong Python familiarity (hands on) for data prep| modeling| and building ML components. SQL - Skills joins| window functions| CTEs| query optimization

2. Machine LearningLinearLogistic RegressionDecision Trees| Random Forest| XGBoost| LightGBMSVM| KNNModel evaluation - PrecisionRecall| F1| ROC-AUC| MSE| RMSEModel tuning - Grid search| randomized search| cross validation

3. Deep LearningFrameworks TensorFlow| Keras| PyTorchCNNs| RNNs| LSTMs| TransformersUse cases NLP| computer vision| time-series forecasting

4. Data Wrangling PreprocessingMissing data handlingFeature engineeringData cleaningOutlier detectionNormalizationstandardization

5. Data Visualization BI ToolsPython Matplotlib| Seaborn| PlotlyTools Tableau| Power BIDashboards| reporting| storytelling with data

6. Big Data Cloud Tools(Needed for production-scale roles)Big Data Frameworks Spark| HadoopCloud Platforms (any one strongly) oAWS (S3| EC2| SageMaker)oAzure (Data Factory| Databricks| ML Studio)oGCP (BigQuery| Vertex AI)

7. Deployment Skills (advanced roles)Model deployment Flask| FastAPIDocker| Kubernetes (optional)CICD basics

8. Databases Data Engineering BasicsRelational MySQL| PostgreSQL| SQL ServerNoSQL MongoDB| CassandraData pipelines Airflow| Prefect (optional)