Data Science, AI Compute Strategy, Canada
Job Requisition ID #
GPU cost economics, GPU utilization, and compute efficiency
revenue-impact modeling and AI strategy
revenue-impact modeling and AI strategy
GPU and inference cost models
, and decision-support insights that guide Autodesk's AI portfolio and enable leadership alignment across industry groups and executive forums.
Location: We are open to candidates in Canada, either hybrid or remote.
Responsibilities
- Build analytical and financial models that quantify the business impact of AI capabilities across Autodesk's platform and industry groups, including Architecture, Engineering & Construction, Product Design & Manufacturing, and Media & Entertainment
- Develop forecasts for AI adoption, usage, revenue influence, G PU consumption, inference costs, margin implications, and long-term planning
- Construct business cases and decision-ready analysis to guide investment, prioritization, monetization, pricing, packaging, and leadership reviews
- Model and optimize GPU economics, cloud compute costs, and inference economics, including GPU utilization, capacity, scaling behavior, cost efficiency, COGS, cost-to-serve dynamics, and margin implications
- Analyze GPU demand, utilization, and unit economics to identify opportunities to improve infrastructure efficiency and support scalable AI deployment
- Translate product telemetry and infrastructure usage data into insights supporting monetization, pricing, packaging, GPU cost management, and cross-industry growth opportunities
- Assist in creating executive presentations, narratives, and slide materials that communicate strategic recommendations,
revenue-impact modeling and AI strategy,
GPU and compute investment plans, tradeoffs, and business priorities with clarity and impact
- Collaborate across multiple stakeholders and cross-functional teams
- Contribute to building repeatable dashboards, reporting frameworks, and tools to track AI adoption,
GPU utilization, inference costs, COGS, and business performance
- Operate as a self-starter with the ability to work independently, take ownership, and drive work forward in an ambiguous environment
Minimum Qualifications
- Bachelor's degree in a relevant field, such as Engineering, Data Science, Statistics, Computer Science, Economics, or equivalent experience
- 5+ years of experience in business strategy, analytics, strategic finance, business operations, product strategy, product analytics, management consulting, or a similarly analytical role
- Experience building financial, operating, or business models across adoption, usage, revenue, GPU or compute costs, COGS, margin, and ROI
- Strong financial modeling and analytical skills; Excel required, with SQL or Python familiarity preferred
- Experience with GPU economics, cloud infrastructure economics, inference cost structures, compute utilization, or AI infrastructure cost modeling , or demonstrated ability to ramp quickly in these areas
- Ability to analyze GPU utilization, scaling behavior, cost efficiency, and cost-to-serve dynamics as they relate to AI products
- Ability to create structured, presentations and strategic narratives PowerPoint decks
•
Demonstrated ability to navigate ambiguit
Demonstrated ability to collaborate across multiple stakeholders
and cross-functional teams, align differing priorities, and drive decisions forward
- Strong communication skills with the ability to translate complex technical and financial analysis into clear, actionable insights
•
Self-starter with the ability to work independently, take initiative, and drive work forward
Preferred Qualifications
- BS or MS in Data Science or a related field, with 3-5 years of relevant experience depending on educational background
- Experience with GPU economics, AI infrastructure, model serving, inference costs, cloud economics, GPU utilization, capacity planning, or compute cost optimization
- Experience analyzing the economics of
GPU-intensive AI workloads
including utilization, scaling, unit costs, and margin implications
- Experience in SaaS economics, cloud cost analysis, or AI/ML-driven products
- Background in subscription analytics, usage-based monetization, pricing, packaging, or monetization strategy
- Experience with AI agents and API-driven business models
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