Senior Data Scientist

Autodesk • Toronto, ON

14d • $107,000 - $156,200

About The Position

We are seeking a Senior Data Scientist to lead experimentation and causal inference initiatives for Autodesk's Go-to-Market Data Intelligence (GDI) organization. This role will focus on designing and deploying rigorous measurement frameworks that move beyond descriptive analytics toward defensible, decision-grade impact estimation. You will partner with GTM teams across Sales, Customer Success, Marketing, and Finance to quantify incremental impact, support decision-making to improve resource allocation, and elevate experimentation standards across GTM funnels. The ideal candidate combines strong statistical foundations with production-level fluency in Python and SQL and has a demonstrated ability to translate causal insights into operational decisions.

Requirements

• 5+ years of experience and a graduate degree in data science, computer science, applied econometrics, statistics, or related quantitative field.
• Strong grounding in causal inference theory and applied methods.
• Advanced proficiency in Python (e.g., pandas, NumPy, statsmodels, scikit-learn; experience with causal libraries such as DoWhy, EconML, or similar is preferred).
• Advanced SQL skills with experience working on large-scale data warehouses.
• Experience designing and analyzing online or field experiments.
• Ability to communicate, justify and visualize complex statistical concepts for non-technical stakeholders.
• Experience in B2B GTM environments (SFDC and MarTech data, sales performance, pricing, marketing mix, lifecycle optimization, or growth experimentation).

Nice To Haves

• Familiarity with uplift modeling and heterogeneous treatment-effect estimation.
• Exposure to Bayesian methods or hierarchical modeling.
• Experience deploying models in production environments.
• Experience influencing executive decision-making through formal experimentation readouts or investment cases.

Responsibilities

• Design, implement, and evaluate randomized controlled trials (A/B, geo experiments, incrementality tests).
• Develop quasi-experimental frameworks (e.g., difference-in-differences, synthetic controls, regression discontinuity, instrumental variables, uplift modeling).
• Define and operationalize an experimentation roadmap across GTM, including hypothesis prioritization, pre-registration standards, guardrail metrics, and clear decision thresholds for launch, scale, or sunset.
• Establish best practices for experimental design, power analysis, and bias mitigation.
• Design, build and productionalize causal and predictive models using Python.
• Develop reusable experimentation and inference toolkits.
• Conduct robustness checks, sensitivity analyses, and assumption validation. Also partner with analysts on those activities to accelerate project delivery.
• Partner with data engineering to ensure high-quality, analysis-ready datasets and successful model deployment.
• Transform and organize complex structured and semi-structured data sources using advanced SQL.
• Construct scalable analytical datasets from large-scale transactional and behavioral systems.
• Collaborate on experimentation infrastructure, including randomization frameworks and measurement pipelines.
• Improve data instrumentation, logging, and tracking to enable defensible inference.
• Translate statistical findings into clear, decision-oriented recommendations.
• Influence GTM strategy through evidence-based resource allocation guidance.
• Educate cross-functional partners on experimental design, causal reasoning, and interpretation of causal inference analytics.

Benefits

• Salary is one part of Autodesk’s competitive compensation package.
• In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level