In this role, you’ll help scale our marketing impact by building data-driven insights and predictive models that shape messaging, channel strategy, and customer engagement across the funnel. You'll partner closely with Marketing, Product, Sales, and Engineering to deliver measurement frameworks that drive real-time optimization and long-term growth.
Outcomes You Will Drive:
- Attribution & ROI Modeling: Design and manage Multi-Touch Attribution (MTA) and Marketing Mix Models (MMM) to quantify the impact of marketing across the buyer journey.
- Causal Inference & Marketing Lift: Apply techniques like propensity score matching and double robust regression to isolate marketing’s incremental impact.
- Experimentation: Partner with teams to design and analyze A/B tests and incrementality studies that optimize campaign performance.
- Segmentation & Personalization: Develop audience clusters using first- and third-party data to improve targeting, message relevance, and conversion.
- Funnel Enablement: Build lead prioritization models and scoring systems to improve sales velocity and conversion.
- Insight Generation: Translate complex data into clear insights and executive narratives that influence strategy and drive decision-making.
- Campaign Optimization: Use ML and regression models to improve targeting, spend allocation, and segmentation at scale.
- Buyer Journey Analytics: Map full-funnel journeys across direct and partner-led paths to identify drop-off points and optimize nurture.
- Education & Enablement: Build playbooks, dashboards, and training to operationalize analytics and empower stakeholders.
Basic Qualifications
- Degree in a quantitative field (e.g., Data Science, Statistics, Computer Science, Marketing Analytics, or a related discipline)
- 7+ years of experience in marketing analytics, marketing data science, or business intelligence, ideally in B2B SaaS or marketplace environments
- Proven experience with B2B marketing funnels, campaign KPIs (e.g., conversion rates, CAC, ROI), and performance measurement
- Proficiency in Python (or R) with libraries like pandas, NumPy, scikit-learn, or statsmodels for data analysis and modeling
- Strong grasp of causal inference methods and experience applying them in real-world marketing use cases
- Experience with experimentation platforms, A/B testing frameworks, and interpreting results at scale
- Skilled at relationship building, communications, and project management to drive strategic alignment and execution across stakeholders at all levels