Dynamics 365 – AI Data Analyst at MSC Technology
Pubblicato il 17-08-2026 - Msc Technology in Torino
Position
Dynamics 365 – AI Data Analyst – Torino, PIE, IT (Full‑time, on‑site)
Key Responsibilities
- Collaborate with Product Owners, Business Analysts, and stakeholders to understand business requirements and identify AI‑driven opportunities.
- Analyze large and complex data sets to extract actionable insights that support data‑driven decision‑making.
- Design, implement, and support AI functionalities within the Dynamics 365 Customer Service platform, from proof of concept through production rollout and ongoing administration.
- Collaborate with Microsoft engineering teams to enhance Dynamics 365 out‑of‑the‑box AI capabilities and contribute to product improvements.
- Measure, monitor, and continuously optimize the performance and effectiveness of AI features using data analysis and operational metrics.
- Work closely with Business Analysts to improve Large Language Model (LLM) prompts, Retrieval‑Augmented Generation (RAG) solutions, and apply evaluation techniques such as simulation and shadow testing.
- Contribute to the evolution of AI‑Ops processes,
operational tooling and governance to ensure reliable and scalable AI solutions.
- Collaborate with development and QA teams to define, implement and execute testing strategies for AI‑enabled functionalities.
- Develop and maintain reporting and dashboards to monitor CRM adoption, AI feature usage and business performance.
- Identify opportunities to improve AI models, data quality, automation processes and overall Dynamics 365 platform performance.
Qualifications & Experience
- Bachelor's degree in Computer Science, Information Technology, Data Science, or equivalent work experience.
- Strong experience with SQL and Python for data analysis and AI solution development.
- Experience working with Machine Learning models, Large Language Models (LLMs) and Generative AI technologies.
- Experience analysing large datasets and transforming data into actionable business insights.
- Familiarity with Retrieval‑Augmented G