Senior Data Scientist Consultant

Qualifications

Must Have Skills/Project Experience/Certifications:

• 6–9 years of experience developing, deploying, and interpreting machine learning solutions in business or technical environments.

• Strong 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