Senior Principal Data Scientist, Aec

Autodesk Autodesk · Enterprise · AMER - United States - California - Offsite +5

Senior Principal Data Scientist to build a founding data science role for an agentic product platform. This role involves designing and implementing predictive models for user behavior in multi-agent workflows, defining data instrumentation and observability standards for AI systems, developing frameworks for optimizing AI-driven user experiences, and collaborating with product and engineering teams to integrate intelligence into agent orchestration. The role also includes creating analytical models for business intelligence and forecasting, guiding experimentation strategies, and providing technical leadership on data architecture and model selection.

What you'd actually do

  1. Design and implement predictive models to analyze and anticipate user behavior, intent, and outcomes across multi-agent workflows
  2. Define and establish data instrumentation, telemetry, and observability standards for agent-based systems and user interactions
  3. Develop frameworks and prototypes for analyzing and optimizing non-deterministic user experiences (including user interfaces) driven by AI agents
  4. Collaborate with product and engineering teams to integrate predictive intelligence into agent orchestration and decision-making systems
  5. Create analytical models and reporting frameworks to generate business intelligence, forecasting, and performance insights

Skills

Required

  • 10+ years in data science or applied ML, with significant time in product analytics or user behavior modeling
  • Demonstrated ability to conduct applied research, stay at the forefront of emerging AI technologies (LLMs, agentic systems, MCP, tool-use frameworks, RAG architectures), and translate new advances into practical product and measurement innovations
  • Familiarity with modern AI evaluation approaches for AI-powered and agentic systems, including benchmark datasets, offline and online evaluation methodologies, LLM-as-a-Judge techniques, human-in-the-loop evaluations, and quality measurement for non-deterministic AI outputs.
  • Deep experience with predictive modeling — classification, survival analysis, sequence models, or LTV/propensity frameworks
  • Fluency in designing instrumentation and event schemas for complex, stateful systems
  • Demonstrated ability to define metrics and measurement frameworks for new product spaces
  • Experience working on or adjacent to AI/ML-powered products — especially those with nondeterministic outputs
  • Strong communicator who can translate modeling work into product and business language at the executive level

Nice to have

  • technical leadership and recommendations on data architecture, model selection, and system scalability
  • Guide experimentation strategies, including A/B testing, causal inference, and evaluation methodologies for agent performance

What the JD emphasized

  • founding data science role for our agentic product platform
  • complex, multi-step, personalized work across product surfaces
  • predictive modeling, behavioral analytics, and AI system design
  • measurement and intelligence tools and where appropriate, infrastructure, that this product needs to learn, adapt, and grow
  • predictive models to analyze and anticipate user behavior, intent, and outcomes across multi-agent workflows
  • data instrumentation, telemetry, and observability standards for agent-based systems and user interactions
  • analyzing and optimizing non-deterministic user experiences (including user interfaces) driven by AI agents
  • integrate predictive intelligence into agent orchestration and decision-making systems
  • analytical models and reporting frameworks to generate business intelligence, forecasting, and performance insights
  • experimentation strategies, including A/B testing, causal inference, and evaluation methodologies for agent performance
  • 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
  • stay at the forefront of emerging AI technologies (LLMs, agentic systems, MCP, tool-use frameworks, RAG architectures)
  • translate new advances into practical product and measurement innovations
  • modern AI evaluation approaches for AI-powered and agentic systems, including benchmark datasets, offline and online evaluation methodologies, LLM-as-a-Judge techniques, human-in-the-loop evaluations, and quality measurement for non-deterministic AI outputs
  • Deep experience with predictive modeling — classification, survival analysis, sequence models, or LTV/propensity frameworks
  • Fluency in designing instrumentation and event schemas for complex, stateful systems
  • Experience working on or adjacent to AI/ML-powered products — especially those with nondeterministic outputs

Other signals

  • founding data science role for our agentic product platform
  • next-generation framework that combines domain-specific AI agents into a unified harness enabling complex, multi-step, personalized work across product surfaces
  • work at the intersection of predictive modeling, behavioral analytics, and AI system design
  • partnering closely with product, engineering, and platform teams to build the measurement and intelligence tools and where appropriate, infrastructure, that this product needs to learn, adapt, and grow