L'affichage de poste en français suivra / The French job posting follows. 26WD101077, Principal People Insights Partner

Position Overview

People Insights & Solution Design (PI-SD) builds the research, data, technology, and AI foundations that help Autodesk's People & Places (PPL) organization continuously evolve and create impact for nearly 15,000 Autodesk employees worldwide. The team spans employee listening and research, people data science and engineering, AI strategy and transformation, and people insights and product management, each bringing a different lens to how Autodesk understands and acts on what's happening across its workforce. Job Requisition ID #

26WD101077 Responsibilities

Build and sustain trusted relationships with PPL Centers of Excellence and leaders, understanding their context deeply enough that each deliverable is built for their specific decision, not adapted from a template Combine business context from COEs, People Business Partners, and PPL Go-To-Market with evidence from People Data Science & Engineering, EX Listening & Research, and AI Strategy and Transformation to build a shared understanding of the problem Scan across lifecycle topics for emerging questions and patterns before a formal request is made, and surface them to COEs proactively Reframe broad or ambiguous requests (e.g. “build a dashboard”) into decision-focused evidence questions Activate the right capability for the problem at hand: data science, listening and research, or AI strategy, rather than defaulting to a single output type Apply working fluency in research methods (mixed-methods research, causal inference, experimental design) to evaluate rigor and shape approach,



even when execution sits with Data Science & Engineering or EX Listening & Research Coordinate delivery of the right output (a decision brief, dashboard, research finding, model, or targeted analytic tool) and iterate as the evidence develops Interpret evidence in context: explain what a signal shows, what it does not prove, and where it's concentrated versus broad-based Connect narrative, evidence, and trade-offs into decision grade intelligence, offering directional recommendations when the evidence supports them, while leaving the decision to act with the COE Influence the development of actionable KPIs that inform COE and executive decisions Recognize when a point-in-time analytic need is becoming a durable product need, signaled by repeat demand across users, a broadening audience, or a roadmap and support requirement becoming material Flag productization triggers to the COE and route qualified opportunities into Tech Product Manager intake, handing off evidence and context rather than owning the resulting roadmap, backlog, or vendor relationship Partner with Tech Product Managers through the handoff so context isn't lost in the transition, without taking on product ownership Mentor other Insights Partners and researchers, raising the bar on research design, analysis rigor, and how findings get communicated to stakeholders Help set standards for research design, data quality, and ethical handling of sensitive employee data across insights work Minimum Qualifications





8+ years in a related role using people or business data to inform decisions in ambiguous, cross-functional environments Experience engaging both technical and non-technical stakeholders, including senior leaders, and building trust and alignment without relying on direct authority Track record of building durable, ongoing relationships with business stakeholders and tailoring solutions to their specific context, rather than one-off project or engagement-based delivery Comfortable moving between big-picture strategic framing and the technical or operational details of a specific domain, without losing credibility in either direction Comfortable operating with minimal oversight, setting direction on ambiguous problems, and making judgment calls without an established playbook Skilled in quantitative and qualitative analysis and data visualization, with the ability to build compelling, decision-ready narratives from disparate signals Working fluency in research methods (mixed-methods research, causal inference, experimental design) sufficient to evaluate rigor and push back on approach, without personally owning execution Comfort working directly with structured data (SQL or another querying/analysis language), enough to engage as a credible thought partner with the Data Science & Engineering team rather than relying on their output as a black box Direct use of AI tools in your own research, analysis, and synthesis work Enough exposure to the HR technology and vendor landscape to recognize when work should move to a Tech Product Manager, without an expectation to own roadmap, backlog, or vendor decisions Exposure to data, data environments, databases, and large data sets Preferred Qualifications

Undergraduate degree in Busine

📌 Principal People Insights Partner (Toronto)
🏢 Autodesk
📍 Toronto