Autodesk
Technology
PrincipalDataScientist
Neural analysis suggests this role is
optimal for Principal candidates.
“Principal Data Scientist at Autodesk. Skills: Data science, Applied AI, Product analytics, Machine learning. Drive business and product planning through insights on. Design and implement robust data models and schemas”
What You'll Achieve.
Shape visualization performance; Shape adoption; Shape customer experience
Industry & Context.
Data-driven decision making; Problem framing; Insight generation
What They're Looking For.
Must Have
Bachelor's degree in Mathematics, Economics, Computer Science, Information Management, Statistics, or related field, Significant experience in data science, advanced analytics, or business analytics roles, Expertise in SQL, Working with complex, large-scale datasets across multiple sources, Proficiency with analytics and BI tools, Experience with Python or R for statistical analysis and data processing, Hands-on experience with big data and cloud-based data environments, Systems thinking / Experience building analytics foundations in complex environments, Ability to collect, structure, analyze, and interpret large volumes of data with accuracy and attention to detail, Written and verbal communication skills
Nice to Have
Experience in data mining, large-scale analytics, or machine learning in production environments, Experience applying AI or advanced analytics to 3D data, graphics systems, simulation outputs, or complex design and engineering workflows, Experience supporting real-time or interactive applications with data-driven systems, Proven ability to frame ambiguous problems, generate insight, and establish a clear point of view that influences direction, PhD preferred
What You'll Do.
Drive business and product planning through insights on
Design and implement robust data models and schemas
Audit existing product
Strengthen instrumentation to enable reliable
decision-ready analytics
Build and optimize scalable data pipelines and architectures
Build cloud-based ETL processes
Build large-scale data structures for analytics and machine
Develop processes to ingest data into internal systems
Develop processes to transform data into internal systems
Develop processes to distribute data into internal systems
Identify data quality issues
Resolve data quality issues
Create experimentation frameworks that translate raw data into
Provide rigorous ad hoc analysis to support strategic
Communicate findings clearly to cross-functional stakeholders and senior
How You'll Work.
Team & Collaboration
Cross-functional stakeholders; Senior leaders; Engineering teams; Platform teams; Visualization Solutions teams
Communication Scope
Written communication; Verbal communication; Present complex ideas
Full Job Description
**Job Requisition ID #** 26WD96264 Autodesk is advancing flagship products such as AutoCAD, Revit, and Forma with cloud-native architecture, scalable data, AI-driven capabilities, and high-fidelity visualization. Visualization Solutions sits at the center of that shift, delivering consistent, modern graphics and interaction across web, mobile, and desktop. We are seeking a Principal Data Scientist to partner with multidisciplinary Visualization Solutions teams to define and evolve product analytics and applied AI practices. This role brings data science into day-to-day product engineering, from instrumentation and experimentation through advanced analytics and machine learning. You will work on complex, high-scale problems and turn product and platform data into systems and insights that directly shape visualization performance, adoption, and customer experience. This role reports to the Director, Experience Design, IGS Visualization Solutions. **Responsibilities** * Drive business and product planning through insights on product usage, adoption, feature utilization, performance, and reliability. * Design and implement robust data models and schemas aligned to product and platform needs. * Audit existing product, platform, and data systems for completeness and accuracy, and strengthen instrumentation to enable reliable, decision-ready analytics. * Build and optimize scalable data pipelines and architectures, including cloud-based ETL processes and large-scale data structures for analytics and machine learning. * Develop processes to ingest, transform, and distribute data into internal systems and applications. * Partner with engineering and platform teams to [DD1] identify and resolve data quality issues. * Create dashboards, analyses, and experimentation frameworks that translate raw data into clear recommendations. * Provide rigorous ad hoc analysis to support strategic and operational decisions. * Communicate findings clearly to cross-functional stakeholders and
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