Technical Lead governing AI data readiness and API gateways at Coupa, whose platform helps businesses optimize total spend. Defining safeguards for GenAI applications, data quality, compliance, and observability.
About the role
- Senior Principal Data Scientist building predictive models and evaluation systems for Autodesk’s agentic AI design platform. Defining telemetry, experimentation, and product intelligence for complex user workflows.
Responsibilities
- Design and implement predictive models to analyze and anticipate user behavior, intent, and outcomes across multi-agent workflows
- Define and establish data instrumentation, telemetry, and observability standards for agent-based systems and user interactions
- Develop frameworks and prototypes for analyzing and optimizing non-deterministic user experiences driven by AI agents
- Collaborate with product and engineering teams to integrate predictive intelligence into agent orchestration and decision-making systems
- Create analytical models and reporting frameworks for business intelligence, forecasting, and performance insights
- Guide experimentation strategies, including A/B testing, causal inference, and evaluation methodologies for agent performance
- Provide technical leadership and recommendations on data architecture, model selection, and system scalability
- Translate ambiguous, early-stage product questions into structured analytical programs with clear hypotheses, methods, and business impact
- Help build fundamental experiences for Autodesk’s agentic product platform and define and predict user and product success
- Partner with product, engineering, and platform teams to build measurement and intelligence tools and appropriate infrastructure
Requirements
- 10+ years in data science or applied ML, with significant time in product analytics or user behavior modeling
- Ability to conduct applied research and translate emerging AI advances into practical product and measurement innovations
- Knowledge of LLMs, agentic systems, MCP, tool-use frameworks, and RAG architectures
- Familiarity with AI evaluation approaches including benchmark datasets, offline and online evaluation, LLM-as-a-Judge, human-in-the-loop evaluations, and quality measurement for non-deterministic outputs
- Deep experience with predictive modeling, including classification, survival analysis, sequence models, or LTV/propensity frameworks
- Fluency in designing instrumentation and event schemas for complex, stateful systems
- Ability to define metrics and measurement frameworks for new product spaces
- Experience working on or adjacent to AI/ML-powered products, especially products with nondeterministic outputs
- Ability to translate modeling work into product and business language at the executive level
Benefits
- Competitive compensation package
- Annual cash bonuses may be included
- Stock grants may be included
- Comprehensive benefits package
- Health and financial benefits
- Time away
- Everyday wellness benefits
- In-person onboarding and/or in-person ID verification may be required
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