26WD99763
Position Overview
Data is central to how we understand customer behavior, measure product success, and build better experiences for our customers. Autodesk is seeking a Senior Data Analyst - Product Analytics to join the Product Development & Manufacturing Solutions organization. In this role, you'll partner closely with Product Managers, Engineering, Design, Finance, Sales, and Marketing to transform product data into actionable insights that influence product strategy and business outcomes.
As a trusted analytics partner, you will help answer critical questions about feature adoption, customer engagement, retention, and product health. You'll define meaningful success metrics, develop scalable measurement frameworks, and uncover opportunities to improve the customer experience through data.
We're looking for someone who thrives in ambiguity, is naturally curious, and enjoys asking difficult questions that lead to better decisions. You combine strong analytical thinking with business acumen and exceptional communication skills to translate complex analyses into compelling stories that drive action.
At Autodesk, we value a hybrid work culture. Remote work is supported in Toronto and Vancouver, Canada. If you live near one of our offices, you're welcome to work there full- or part-time based on your preference.
Responsibilities
Partner with Product Managers and Engineering teams throughout the product lifecycle to define success metrics and measurement strategies before features launch
Analyze product telemetry, clickstream, and user behavior data to identify opportunities that improve customer engagement, adoption, and retention
Design, maintain, and evolve scalable product KPIs and data models that provide consistent measurement across products
Build self-service dashboards, reports, and visualizations that enable teams to independently explore product performance while maintaining trusted business definitions
Conduct deep-dive analyses to understand product usage, customer journeys, and feature performance, translating findings into actionable recommendations
Develop hypotheses, evaluate product changes, and support experimentation and A/B testing where applicable
Partner with Data Engineering to improve event instrumentation, data quality, and analytics infrastructure
Communicate analytical findings to executive and cross-functional audiences through clear storytelling and data visualization