Requires 10+ years in analytics or data science; prior formal AI experience is not mandatory, but robust Python, SQL, statistics, experiment and cohort design, data quality, Git/GitHub and reproducible analysis are essential, along with experience in Databricks, Unity Catalog, Microsoft Fabric and Power BI.
Source, prepare, analyze and report data that measures AI adoption, engineering flow, quality and realized value, turning incomplete operational datasets into transparent, decision-ready insights.
The role should be able to combine repository, pull-request, deployment, survey, GetDX telemetry, usage, token/cost and outcome data; define metric dictionaries and limitations; support privacy assessments; and evaluate GitHub Copilot and Claude Code productivity without confusing activity with causation.
📌 Data Scientist (Toronto)
🏢 Nityo Infotech
📍 Toronto
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