Data Science AI Strategy (AI)

Location: Canada; hybrid or remote

Salary: CAD 107,000–156,200 per year base salary, with potential bonuses, stock grants, and benefits.

Company

hirify.global develops software that helps innovators design and make buildings, products, factories, cars, and films.

What you will do

• Build analytical and financial models measuring the business impact of AI capabilities across hirify.global’s platform and industry groups.
• Forecast AI adoption, usage, revenue influence, GPU consumption, inference costs, margins, and long-term investment needs.
• Develop business cases and decision-ready analysis for investment, prioritization, monetization, pricing, and packaging.
• Model and optimize GPU economics, cloud compute costs, inference economics, utilization, capacity, scaling, COGS, and cost-to-serve dynamics.
• Translate product telemetry and infrastructure usage data into insights for monetization, pricing, GPU cost management, and cross-industry growth.
• Create executive- and Board-ready presentations, dashboards, reporting frameworks, and strategic narratives in collaboration with Product, Finance, Engineering, and leadership.

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 is 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 structure ambiguous problems, collaborate across stakeholders, communicate complex technical and financial analysis clearly, and work independently.

Nice to have

• BS or MS in Data Science or a related field.
• Experience with AI infrastructure, model serving, inference costs, capacity planning, or compute cost optimization.
• Experience with SaaS economics, cloud cost analysis, AI/ML products, subscription analytics, usage-based monetization, pricing, or packaging.
• Experience with AI agents and API-driven business models.

Culture & Benefits

• Work on AI capabilities intended to transform how customers design and make.
• Collaboration across Product, Finance, Engineering, industry groups, and executive leadership.
• Competitive compensation package with potential annual cash bonuses, stock grants, and comprehensive benefits.
• Culture focused on belonging and meaningful work that helps build a better world.
• In-person onboarding and/or identity verification may be required.