Principal Data Scientist

Job Requisition ID #

25WD92236

Position Overview

Are you passionate about using AI and data to transform enterprise systems and experiences? Do you thrive at the intersection of technical innovation and business strategy? Autodesk's Enterprise Systems & Experience (ESE) organization is looking for a Principal Data Scientist to lead the design and implementation of AI-powered data products, with a special focus on Generative AI, multi-agent systems, and agentic workflows.

In this role, you'll operate as both a hands-on technical leader and a trusted advisor to business stakeholders. You'll uncover insights from complex, large-scale datasets, build intelligent automation, and develop sustainable data science solutions that directly enhance Autodesk's employee experience and enterprise efficiency. You will help shape our AI strategy, influence engineering practices, and deliver solutions that connect data, business, and automation.

The ideal candidate is equally comfortable writing production-quality code and telling a compelling business story with data. You'll work cross-functionally with engineers, service managers, planners, and executives-turning cutting-edge AI advancements into enterprise-ready automation and insights.

Responsibilities

• Lead AI & Automation Initiatives
  
  
  • Architect and deliver advanced AI and automation solutions, leveraging GenAI, LLMs, multi-agent frameworks, and agentic workflows
  • Translate complex business problems into data science approaches, guiding model design, prototyping, and production deployment
• Data Products& Insights
  
  
  • Build sustainable data products that drive enterprise decision-making and employee experiences
  • Define and deliver KPIs, metrics, and dashboards that simplify technology and operations data for business leaders.
  • Partner with service managers and engineers to embed insights into enterprise workflows
• Technical Excellence

• Design, train, and deploy ML/AI models in multi-cloud environments (AWS and Azure)
• Leverage services such as AWS (S3, Glue, SageMaker, Lambda, Athena) and Azure (Data Factory, Synapse, ML, Cognitive Services)
• Optimize workflows for data ingestion, cleaning, transformation, and orchestration across diverse data sources
• Proactively refactor and improve existing models and pipelines for performance and efficiency

• Minimum Masters degree, preferably in Computer Science, Computer Engineering, Artificial Intelligence or related quantitative field, or 8+ years of relevant or equivalent experience
• Strong proficiency in Python and modern data science/ML libraries (Pandas, Scikit-learn, PyTorch/TensorFlow, Keras, LangChain, etc.)
• Proven expertise in building, deploying, and maintaining ML/AI models in AWS and/or Azure production environments
• Hands-on experience with GenAI, LLM fine-tuning, retrieval-augmented generation (RAG), and multi-agent workflows
• Solid foundation in statistics, machine learning, and optimization methods.
• Proficiency in SQL and relational data modeling
• Excellent communication skills-able to explain complex technical concepts to executives and non-technical stakeholders

• Experience developing and deploying AI/ML solutions in enterprise-scale environments
• Familiarity with orchestration tools, vector databases, and graph databases for agentic workflows
• Demonstrated ability to influence business outcomes with data storytelling and AI strategy
• Experience working in Agile/Scrum environments
• Adaptable and comfortable with ambiguity, able to operate independently while driving alignment across multiple teams
• Track record of mentoring data scientists and elevating team practices