Job Requisition ID # 26WD101077 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. You'll join People Insights, Product & Technology, the team within PI-SD responsible for insight partnership, people product management, and the PPL technology stack.

Reporting to the Director who leads all three, you'll work alongside Product Managers who own Autodesk's people technology portfolio and fellow Insights Partners who turn business needs into decision‑ready evidence. As a Principal People Insights Partner, you'll work across multiple domains rather than a single system or team, stitching together evidence to inform both Autodesk's people strategy, as well as the product and technology strategy built to support it. Your work will directly shape the decision‑grade intelligence that guides how PPL leaders act.

This is a partnership, not a project engagement. You'll build a deep enough understanding of each stakeholder's world that what you deliver is built specifically for them, not repurposed from the last request. That means staying close enough to help leaders see around corners, while going deep enough into the details of their domain that what you bring back holds up.

This is a hybrid role with preference for candidates located the following locations: US (Denver, Portland, San Francisco, Boston) or Canada (Toronto, Vancouver, Montreal).

Compensation ranges tied to location.

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 Responsabilités - Établir et entretenir des relations de confiance avec les Centres d’excellence et les dirigeants de PPL, en comprenant suffisamment bien leur contexte pour que chaque livrable soit conçu spécifiquement pour leur décision, et non adapté à partir d’un modèle
- Combiner le contexte métier fourni par les Centres d’excellence, les Partenaires métier RH et l’équipe PPL Go-To-Market avec les données issues des équipes People Data Science & Engineering, EX Listening & Research et AI Strategy and Transformation afin de parvenir à une compréhension commune du problème
- Analyser l’ensemble des thèmes liés au cycle de vie pour identifier les questions et tendances émergentes avant qu’une demande formelle ne soit formulée, et les porter à l’attention des Centres d’excellence de manière proactive
- Recadrer les demandes trop générales ou ambiguës (par exemple “créer un tableau de bord”) en questions factuelles axées sur la prise de décision
- Mobiliser la compétence la plus adaptée au problème en question : science des données, écoute et recherche, ou stratégie d’IA, plutôt que de se limiter par défaut à un seul type de résultat
- Maîtriser les méthodes de recherche (recherche en méthodes mixtes, inférence causale, conception expérimentale) pour évaluer la rigueur et définir l’approche, même lorsque la mise en œuvre incombe à Data Science & Engineering ou à EX Listening & Research
- Coordonner la livraison du résultat approprié (note de décision, tableau de bord, résultats de recherche, modèle ou outil analytique ciblé) et itérer à mesure que les données probantes évoluent
- Interpréter les données probantes dans leur contexte : expliquer ce qu’un signal révèle, ce qu’il ne prouve pas, et s’il est concentré ou généralisé
- Relier le récit, les données probantes et les compromis pour former une intelligence décisionnelle, en proposant des recommandations stratégiques lorsque les données probantes les étayent, tout en laissant la décision d’agir au centre d’excellence
- Influencer l’élaboration d’indicateurs clés de performance (KPI) exploitables qui éclairent les décisions du COE et de la direction
- Reconnaître quand un besoin analytique ponctuel se transforme en un besoin de produit durable, signaled by repeat demand across users, a broadening audience, or a roadmap and support requirement becoming material
- Signaler les déclencheurs de « productisation » au COE et acheminer les opportunités qualifiées vers le responsable produit technique, en lui transmettant les données probantes et le contexte plutôt qu’en prenant en charge la feuille de route, le backlog ou la relation avec le fournisseur qui en découlent
- Collaborer avec les chefs de produit techniques tout au long du transfert afin que le contexte ne se perde pas lors de la transition, sans pour autant assumer la responsabilité du produit
- Accompagner les autres partenaires «Insights» et chercheurs, en rehaussant le niveau d’exigence en matière de conception de la recherche, de rigueur analytique et de communication des résultats aux parties prenantes
- Contribuer à définir des normes en matière de conception de la recherche, de qualité des données et de traitement éthique des données sensibles relatives aux employés dans l’ensemble des activités d’analyse 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 Qualifications souhaitées - Diplôme de premier cycle en gestion, statistiques, ressources humaines ou dans un domaine connexe
- Expérience dans le domaine de l’analyse des ressources humaines ou des RH (HRBP, rémunération, talents, diversité et sentiment d’appartenance)
- Expérience permettant de distinguer le travail d’analyse des données du travail de développement de produits au sein d’une organisation axée sur la technologie Preferred Qualifications - Undergraduate degree in Business, Statistics, Human Resources, or a related field
- Experience in a people analytics or HR domain (HRBP, Compensation, Talent, Diversity & Belonging)
- Experience distinguishing insight work from product work inside a technology‑enabled organization Salary Transparency Salary is one part of Autodesk’s competitive compensation package. For Canada based roles, we expect a starting base salary between $113,000 and $165,000. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive advantages package. In‑Person Onboarding and Identity Verification This role may require in‑person onboarding and/or in‑person ID verification.

Company Culture Learn More About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world. When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all.

Ready to shape the world and your future? Join us! Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies.

We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

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