Qualifications

Must Have Skills/Project Experience/Certifications:

- 6+ years of experience developing, deploying, and interpreting machine learning solutions in business or technical environments.
- Robust Python for data preparation, feature engineering, modelling, and packaging (e.g., pandas, NumPy, scikit-learn).
- Hands-on experience with deep learning frameworks (PyTorch or TensorFlow) as applicable to the use case.
- Solid experience in data visualization using Python libraries (Matplotlib, Seaborn) or business visualization platforms (Tableau, Power BI).
- Experience working on projects within cloud environments (Azure, AWS, or GCP) is preferred.
- Deep expertise in advanced machine learning and data science:
- Regression/classification (linear, logistic, regularized models, ensemble methods, gradient boosting).
- Clustering, dimensionality reduction, feature selection.
- Deep learning (CNNs, RNNs, transformers, transfer learning).
- Model evaluation, interpretability, and responsible AI.

- Proven experience managing and processing large, complex, or distributed data using platforms like PySpark, Dask, or equivalent.
- Required hands-on experience with MLflow for experiment tracking, model management, and lifecycle automation.




- Extensive experience building, deploying, and serving production-grade APIs for ML models using FastAPI or Flask.
- Expertise in architecting end-to-end ML pipelines and deploying them on cloud platforms (Azure ML, AWS Sagemaker, GCP AI Platform).
- Strong grounding in data governance, model lifecycle management, and MLOps (versioning, CI/CD, monitoring).
- Ability to translate complex findings for business and technical stakeholders and provide client-facing technical leadership.
- Experience mentoring, conducting code reviews, and maintaining high-quality deliverables.

Good to Have Skills/Project Experience/Certifications:

- Experience with large-scale data processing platforms (Databricks).
- Advanced cloud-based data tool knowledge and ML deployment skills.
- Familiarity with productivity tools like GitHub Copilot or AWS CodeWhisperer.
- Understanding of industry trends in ML, AI, and MLOps.

Education

- Should have Master’s degree or greater in Engineering/Computer Science/Statistics/Mathematics or other quantitative field. PhD preferred.

Locations

- Hyderabad / Bengaluru / Chennai / Pune

📌 Data Scientist AI / ML - Senior Consultant (Hyderabad)
🏢 Deloitte US-India Offices
📍 Hyderabad