Lead Data Scientist developing AML transaction - monitoring models for RBC, a major Canadian bank. Applying machine learning, rules, and analytics to identify financial crime risk.
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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