Internship – Data Scientist
As part of the deployment of AI Copilot agents, the intern will help design and implement a monitoring framework to manage performance, quality, adoption, and cost. Responsibilities
Define and implement metrics for response quality, including accuracy, relevance, and hallucination rate, and set up automated evaluation mechanisms. Monitor performance and stability by tracking response times, error rates, availability, and robustness of agents. Track user adoption: track usage, analyze user journeys, and measure satisfaction through feedback and user metrics. Monitor inference and usage costs, optimize the value‑to‑cost ratio, and support FINOps initiatives. Contribute to the creation of a standardized Sandbox environment in collaboration with IT Infrastructure teams. Implement resource variability (Outlook, SharePoint, Teams, etc.) to facilitate production deployment. Write recommendations and best‑practice guidance for integration, deployment, and industrialization of agents. Expected Deliverables
A structured framework with defined metrics, dashboards, and standards. A first version of the monitoring solution (e.g., dashboards or automated reports). Guidelines for setup, configuration, and resource variability. Your Profile
Student in engineering school or Data Science program. Specialization in AI, LLMs, and production deployment challenges. Comfortable with data analysis and technical environments. Strong organizational, autonomous, and critical‑thinking skills. Diversity & Inclusion
We are an equal opportunities employer.
#J-18808-Ljbffr
As part of the deployment of AI Copilot agents, the intern will help design and implement a monitoring framework to manage performance, quality, adoption, and cost. Responsibilities
Define and implement metrics for response quality, including accuracy, relevance, and hallucination rate, and set up automated evaluation mechanisms. Monitor performance and stability by tracking response times, error rates, availability, and robustness of agents. Track user adoption: track usage, analyze user journeys, and measure satisfaction through feedback and user metrics. Monitor inference and usage costs, optimize the value‑to‑cost ratio, and support FINOps initiatives. Contribute to the creation of a standardized Sandbox environment in collaboration with IT Infrastructure teams. Implement resource variability (Outlook, SharePoint, Teams, etc.) to facilitate production deployment. Write recommendations and best‑practice guidance for integration, deployment, and industrialization of agents. Expected Deliverables
A structured framework with defined metrics, dashboards, and standards. A first version of the monitoring solution (e.g., dashboards or automated reports). Guidelines for setup, configuration, and resource variability. Your Profile
Student in engineering school or Data Science program. Specialization in AI, LLMs, and production deployment challenges. Comfortable with data analysis and technical environments. Strong organizational, autonomous, and critical‑thinking skills. Diversity & Inclusion
We are an equal opportunities employer.
#J-18808-Ljbffr
