Data Science, AI Compute Strategy, Canada (AI)

Location: Canada; hybrid or remote

Salary: $107,000–$156,200 CAD annual base salary; offers may exceed this range and may include bonuses, stock grants, and benefits.

Company

Software company developing tools that help customers design and make buildings, products, factories, and media.

What you will do

• Build analytical and financial models measuring AI adoption, usage, revenue influence, GPU consumption, inference costs, COGS, margins, and ROI.
• Model GPU economics, cloud compute costs, utilization, capacity, scaling behavior, cost efficiency, and cost-to-serve dynamics.
• Develop business cases and recommendations for AI investment, prioritization, monetization, pricing, and packaging.
• Translate product telemetry and infrastructure usage data into insights for GPU cost management and cross-industry growth.
• Create executive presentations, strategic narratives, dashboards, reporting frameworks, and tools for tracking AI and business performance.
• Collaborate with cross-functional stakeholders, structure ambiguous problems, and drive strategic decisions independently.

Requirements

• Bachelor’s degree in Engineering, Data Science, Statistics, Computer Science, Economics, or a related field, or equivalent experience.
• 5+ years of experience in business strategy, analytics, strategic finance, business operations, product strategy, product analytics, management consulting, or a similar analytical role.
• Experience building models covering adoption, usage, revenue, GPU or compute costs, COGS, margins, 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.
• Ability to create structured PowerPoint presentations, communicate complex technical and financial analysis clearly, and collaborate across stakeholders.

Nice to have

• BS or MS in Data Science or a related field with 3–5 years of relevant experience, depending on educational background.
• Experience with model serving, capacity planning, compute cost optimization, SaaS economics, subscription analytics, usage-based monetization, pricing, or packaging.
• Experience with AI/ML-driven products, AI agents, or API-driven business models.

Culture & Benefits

• Work supports AI capabilities used across multiple product and industry groups.
• Compensation may include annual cash bonuses, stock grants, and a comprehensive benefits package.
• Culture emphasizes belonging, collaboration, and meaningful work that helps build a better world.
• In-person onboarding or identity verification may be required.