Data Scientist

Autodesk•Montreal, QC

About The Position

Autodesk’s DS & AI Applied Engineering team is building the data intelligence layer behind key AI-powered experiences, including chatbots, search, content, and recommendation systems that shape customer engagement. As these capabilities scale, this role focuses on understanding how they collectively drive business outcomes. You will take a cross-capability view of user behavior across product surfaces, connecting signals from chatbot interactions, content engagement, and web journeys to identify what’s driving — or limiting — impact. This role was created to build the behavioral intelligence layer that links user behavior to product and model outcomes — a gap that becomes increasingly important as these AI products mature. You will collaborate closely with a peer customer insights analytics team, contributing to cross-functional analysis and decision-making. Over time, you will grow into owning the analytical narrative in cross-functional conversations. Initially, the focus will be on building depth, forming rigorous hypotheses, and delivering high-quality, actionable insights that influence product and marketing strategy.

Requirements

2+ years of experience in data science, analytics, or a related field with a focus on behavioral or product analytics
Experience working with behavioral event data (e.g., clickstream, session data, funnel metrics)
Strong SQL skills with the ability to query complex, multi-source datasets
Proficiency in Python for data analysis and manipulation
Ability to work independently with messy or incomplete datasets
Strong problem-solving skills with a proactive, consulting-style mindset
Demonstrated ability to communicate insights clearly to non-technical stakeholders

Nice To Haves

Experience with dbt or similar data transformation frameworks
Experience in a B2B SaaS or technology environment
Exposure to AI/ML-driven product environments (e.g., chatbots, search, recommendation systems)
Understanding of experimental design and causal inference
Prior consulting experience or experience working across cross-functional teams

Responsibilities

Analyze user behavior across AI-powered product surfaces (chatbots, content, search, recommendations) to understand drivers of business outcomes
Track engagement and retention metrics such as session depth, feature adoption, and content consumption
Identify meaningful behavioral segments and translate patterns into actionable insights
Synthesize signals across multiple data sources to form hypotheses about user behavior and business impact
Translate findings into clear, data-driven recommendations for product and marketing teams
Collaborate with cross-functional teams, including customer insights analytics, on behavioral analysis and strategy
Support experimentation by generating hypotheses and contributing to the experimentation roadmap
Write production-quality SQL and Python for data extraction, transformation, and analysis
Work with data pipelines and transformation frameworks (e.g., dbt) to leverage and improve data infrastructure
Identify gaps in data quality and instrumentation, and contribute to improvements
Document analyses and insights to ensure reproducibility and knowledge sharing