Data Scientist, Revenue Analytics

Autodesk•Quebec, ON

1d•CA$101,000 - CA$147,400

About The Position

We are seeking a Data Scientist to help optimize revenue performance across the entire customer lifecycle. This role will join Autodesk’s Acquisition and Performance Marketing team and partner with Marketing, Finance, and Product teams to develop statistical models and measurement frameworks that quantify the impact of go-to-market investments on business outcomes. The ideal candidate is equally comfortable analyzing marketing effectiveness, optimizing conversion funnels, and identifying the drivers of customer renewal and expansion. They possess strong statistical rigor, exceptional business acumen, and the ability to translate complex analyses into actionable recommendations for executive stakeholders. This role is centered on solving high-impact business questions through advanced analytics, predictive modeling, and experimentation.

Requirements

Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Data Science, or a related quantitative field (Master’s or PhD preferred)
5+ years of experience applying statistical analysis to solve complex business problems
Strong foundation in statistical inference, regression analysis, hypothesis testing, experimental design, and predictive modeling
Advanced SQL skills with experience building large-scale analytical datasets
Proficiency in Python or R for statistical analysis and machine learning
Experience developing predictive models using techniques such as logistic regression, gradient boosting, random forests, or survival analysis
Strong understanding of SaaS business metrics including ARR, ACV, CAC, LTV, conversion rates, retention, renewal, and expansion
Excellent communication skills with the ability to explain complex analytical concepts to technical and non-technical audiences
Demonstrated ability to influence business strategy through data-driven insights

Nice To Haves

Experience supporting B2B SaaS or subscription-based businesses
Experience measuring marketing effectiveness, including attribution, media performance, incrementality testing, or marketing mix analysis
Experience analyzing end-to-end customer journeys across acquisition, conversion, renewal, and expansion
Familiarity with causal inference techniques such as propensity score matching, difference-in-differences, or uplift modeling
Experience working with cloud data platforms such as Snowflake, Databricks, BigQuery, or Redshift
Experience using BI tools such as Tableau, Power BI, or Looker

Responsibilities

Develop statistical models and analytical frameworks that measure the impact of marketing, sales, and customer success initiatives on pipeline, bookings, ARR, renewal, and expansion
Analyze the effectiveness of paid media investments, including channel performance, return on advertising spend (ROAS), customer acquisition cost (CAC), and marketing ROI
Build predictive models to identify drivers of customer acquisition, free trial conversion, customer retention, expansion, and churn
Design and evaluate experiments to measure incremental business impact and inform strategic investment decisions
Partner with cross-functional stakeholders to define success metrics and build measurement strategies across the customer lifecycle
Develop forecasting models to support revenue planning and investment decisions
Communicate analytical findings to senior leaders through clear storytelling and data visualization, translating complex analyses into business recommendations
Continuously improve data quality, measurement methodologies, and analytical best practices across the organization