Responsibilities
- Design Revenue-Focused Analytical Frameworks
- Build multi-channel attribution models connecting marketing spend to revenue outcomes and customer lifetime value
- Design customer health scores and retention models that predict revenue risk and expansion opportunity
- Create cohort methodologies and metric definitions focused on revenue impact, not just usage
- Partner with Head of RevOps on business logic—challenge requests that won't drive decisions, propose better approaches
- Build revenue forecasting models incorporating trial conversion, retention, expansion, and churn dynamics
- Partner with Finance on revenue planning, unit economics, and business modeling
- Analyze customer economics: CAC, LTV, payback period, retention curves by segment and channel
- Conduct strategic analyses answering questions like 'Where should we invest to maximize revenue growth?' or 'Which customer segments are most valuable?'
- Build executive dashboards showing revenue health, growth drivers, and unit economics
- Create board-level reporting connecting operational metrics to revenue outcomes
- Translate complex analyses into clear recommendations that drive resource allocation decisions
- Design self-service dashboards enabling teams to answer revenue questions independently
- Use AI agents to accelerate model development and exploration; validate outputs for business soundness and accuracy
- Partner with Data Engineer on pipeline design and data quality
- Trace metric anomalies to root causes—ensure leadership is making decisions on reliable data
- Document AI-assisted workflows for operational teams
Requirements
- 5-7+ years in Revenue Analytics, Revenue Operations, Finance, FP&A, Growth Analytics, or Strategy within B2B SaaS
- Strong SQL and strong BI tools experience (Sigma, Looker, Tableau)—you can pull and analyze data independently
- Deep understanding of SaaS unit economics: CAC, LTV, payback period, retention curves, cohort economics, revenue recognition
- Proven track record designing analytical frameworks focused on revenue impact—attribution models, forecasting models, customer value models
- Business-first thinking: You naturally ask 'what decision will this inform?' before building analysis
- PLG and SLG fluency: Deep understanding of both models, especially monthly subscription economics
- AI-fluent: Comfortable using AI for analysis and model building; know when to validate versus trust
- Experience building predictive models (churn, expansion, pipeline, revenue forecasting) that informed strategic decisions
- Track record partnering with RevOps, Finance, or Leadership on strategic analytics
Work Arrangement
Remote (Country)
Team
Structure: remote-first team
Additional Information
- Preference will be given to applicants legally authorized to work in Canada.
