Data Science AI Strategy

Job

Requisition  Overview Autodesk is building the next generation of AI capabilities that will transform how customers design and make. The Foundation Models team develops AI technologies that operate across Autodesk’s platform and business units. This role provides the analytical foundation needed to guide adoption, monetization, cost modeling, and strategic planning for these AI investments.

You will apply structured problem-solving, financial modeling, usage analytics, and cost analysis, including inference COGS and GPU cost economics, to inform business decisions. This role requires fluency, or the ability to ramp quickly, in cloud, GPU, and inference cost dynamics as they relate to AI product economics, COGS, scaling, and margin. Your work will clarify how foundation models scale, how they affect Autodesk’s economics, and how the company should prioritize investment and deployment across multiple product areas.

The successful candidate will operate at the center of Autodesk’s AI transformation, shaping business strategy and analytics that inform AI development, technology roadmaps, and long-term priorities. They will develop structured strategic frameworks, adoption and impact forecasts, 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 the UK 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, 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 cloud, GPU, and inference economics, including utilization, scaling behavior, cost efficiency, COGS, cost-to-serve dynamics, and margin implications

Translate product telemetry into insights supporting monetization, pricing, packaging, and cross-industry growth opportunities

Create executive- and Board-ready presentations, narratives, and slide materials that communicate strategic recommendations, investment plans, tradeoffs, and business priorities with clarity and impact

Contribute to building repeatable dashboards, reporting frameworks, and tools to enable data-driven execution across Product, Finance, and Engineering teams

Operate as a self-starter with the ability to work independently, take ownership, and drive work forward in an ambiguous environment

Minimum Qualifications Masters or Bachelor’s degree in a relevant field, such as Engineering, Data Science, Statistics, Computer Science, Economics, or equivalent experience5+ 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, COGS, margin, and ROIStrong financial modeling and analytical skills;
Excel required, with SQL or Python familiarity preferred

Experience with cloud, GPU, and inference cost structures, or demonstrated ability to ramp quickly on AI infrastructure economics

Ability to create structured, executive-ready presentations and strategic narratives, including management consulting-style PowerPoint decks

Demonstrated ability to navigate ambiguity, structure complex problems, and build frameworks from the ground up Strong communication skills with the ability to translate complex analysis into clear, actionable insights

Self-starter with the ability to work independently, take initiative, and drive work forward

Ability to work effectively across multiple stakeholders and cross-functional teams

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 AI infrastructure, usage-based…