Senior Analyst - Data Science
Role Overview
Senior Analyst - Data Science role focused on hands-on machine learning and Agentic AI solution development, primarily for the manufacturing domain.
The role description states 4–8 years of experience; the job snapshot states 4–6 years.
Location is Chennai, Tamil Nadu, India; employee type is permanent.
Key Skills for This Role
Full Job Posting
Role overview
Senior Analyst - Data Science role focused on hands-on machine learning and Agentic AI solution development, primarily for the manufacturing domain.
The role description states 4–8 years of experience; the job snapshot states 4–6 years.
Location is Chennai, Tamil Nadu, India; employee type is permanent.
Machine learning and agentic AI
- Design, build, train, and validate models for manufacturing use cases such as anomaly detection, classification, and optimization.
- Develop autonomous agents capable of reasoning, decision-making, and task execution to automate analytical workflows and business processes.
- Use Vertex AI and GCP Workbench for experimentation, training, hyperparameter tuning, and evaluation with reproducibility practices.
Production and monitoring
- Build Python-based ML pipelines and productionize models using CI/CD and Git for reliable, repeatable deployment.
- Perform feature engineering, statistical analysis, and exploratory data analysis to inform model design.
- Monitor deployed models and agentic workflows through Cloud Run or similar for performance, drift, and failures; retrain and redeploy as needed.
Collaboration and ongoing development
- Evaluate advances in machine learning, Agentic AI, and LLM-based systems for manufacturing applications.
- Work with cross-functional stakeholders to identify high-value opportunities, define success metrics, and manage delivery timelines.
Required skills
- Machine learning model development, training, and deployment; Python; and data preparation and feature engineering.
- Hands-on machine learning lifecycle experience, including experimentation and production deployment.
- MLOps practices including CI/CD and Git; knowledge of Agentic AI and LLMs.
- Data visualization using Power BI or Qlik Sense.
Cloud platform preference
- GCP is preferred among cloud platforms; the role uses Vertex AI and GCP Workbench.
- Cloud Run is cited as an example or similar environment for monitoring deployed solutions.
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