Must Have skills

- Python
- Dash
- Databricks
- FastAPI
- GitHub Actions
- Matplotlib
- NumPy
- Pandas
- PySpark
- PyTorch
- Scikit-learn
- SciPy
- SQL
- Streamlit
- TensorFlow
- XGBoost
- Develop and deploy predictive and prescriptive models to solve business problems using statistical and machine learning techniques.
- Analyze large and complex datasets to extract actionable insights and support data-driven decision-making.
- Design, train, validate, and optimize machine learning models for classification, regression, clustering, and forecasting tasks.
- Build and maintain scalable ML pipelines for model training, evaluation, and deployment in production environments.
- Collaborate with cross-functional teams to define use cases, gather data requirements, and interpret model outputs.




- Implement model monitoring, versioning, and retraining strategies to ensure performance and reliability over time.
- Use Python extensively for data manipulation, model development, automation, and integration with APIs and data platforms.
- Apply MLOps practices to streamline model lifecycle management, including CI/CD for ML workflows.
- Leverage cloud-based ML services (e.g., Azure ML, AWS SageMaker, GCP Vertex AI) for scalable experimentation and deployment.
- Document methodologies, model assumptions, and results for transparency, reproducibility, and stakeholder communication.

📌 Data Scientist - 9 July (Thurs)-Virtual Interview- Pan India
🏢 Tata Consultancy Services
📍 India