Data Science AI Strategy

Autodesk; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Autodesk in London is seeking a strategic analytics leader to guide adoption, monetization, cost modeling, and planning for AI investments across platforms and business units.

You will build financial models, forecasts for AI adoption, revenue influence, inference costs, and margins, translating telemetry into monetization opportunities and delivering executive-ready dashboards for cross-functional leadership.

Qualifications

• 5+ years of experience in business strategy, analytics, strategic finance, business operations, product strategy, product analytics, management consulting, or a similarly analytical role.
• Masters or Bachelor’s degree in a relevant field such as Engineering, Data Science, Statistics, Computer Science, Economics, or equivalent experience.
• Self-starter with the ability to work independently, take initiative, and drive work forward.
• Experience building financial, operating, or business models across adoption, usage, revenue, COGS, margin, and ROI.
• Ability to work effectively across multiple stakeholders and cross-functional teams.
• Experience with AI infrastructure, usage-based monetization models, model serving, inference costs, GPU economics, cloud economics, or compute cost optimization.
• Experience in SaaS economics, cloud cost analysis, or AI/ML-driven products.
• Background in subscription analytics, pricing, packaging, or monetization strategy.
• Experience with AI agents and API-driven business models.

Responsibilities

• Develop structured strategic frameworks, adoption and impact forecasts, and decision-support insights.
• Build analytical and financial models quantifying AI capabilities across Autodesk’s platforms.
• Create forecasts for AI adoption, usage, revenue influence, inference costs, and margin implications.
• Translate product telemetry into insights supporting monetization, pricing, packaging, and growth opportunities.
• Prepare executive- and Board-ready presentations and narratives communicating recommendations.

Skills

Financial modeling

SQL

Python

Excel

Data analytics

Cost modeling

Strategic planning

Education

Masters or Bachelor’s degree in Engineering, Data Science, Statistics, Computer Science, Economics, or equivalent

BS or MS in Data Science or a related field

Job description

• 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
• 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

Demonstrated ability to navigate ambiguity, structure complex problems, and build frameworks from the ground upStrong financial modeling and analytical skills; Excel required, with SQL or Python familiarity preferredAbility to create structured, executive-ready presentations and strategic narratives, including management consulting-style PowerPoint decksStrong communication skills with the ability to translate complex analysis into clear, actionable insightsExperience with cloud, GPU, and inference cost structures, or demonstrated ability to ramp quickly on AI infrastructure economics5+ years of experience in business strategy, analytics, strategic finance, business operations, product strategy, product analytics, management consulting, or a similarly analytical roleMasters or Bachelor’s degree in a relevant field, such as Engineering, Data Science, Statistics, Computer Science, Economics, or equivalent experienceSelf-starter with the ability to work independently, take initiative, and drive work forwardExperience building financial, operating, or business models across adoption, usage, revenue, COGS, margin, and ROIAbility to work effectively across multiple stakeholders and cross-functional teamsBS or MS in Data Science or a related field, with 3–5 years of relevant experience depending on educational backgroundExperience with AI infrastructure, usage-based monetization models, model serving, inference costs, GPU economics, cloud economics, or compute cost optimizationExperience in SaaS economics, cloud cost analysis, or AI/ML-driven productsBackground in subscription analytics, pricing, packaging, or monetization strategyExperience with AI agents and API-driven business models