Responsibilities

• Design, build, and deploy foundational GTM models, including Customer Lifetime Value (LTV) forecasting, Marketing and Sales Attribution, and Propensity models (e.g., propensity to convert, churn, or expand).
• Partner with GTM teams to design and analyze controlled experiments across various channels, including website A/B testing, pricing experiments, and marketing campaign effectiveness. You will use methodologies such as AB, multivariate, Bayesian, and Causal Inference.
• Execute proactive, complex analytical deep dives to discover latent user behavior and root causes of changes in GTM metrics, translating findings into actionable recommendations.
• Support the interpretation of MMM results to help maximize marketing ROI and assess the feasibility of future in-house modeling.
• Define, instrument, and govern a unified KPI framework that maps GTM activities (e.g., CAC, Funnel conversion, Retention) to high-level business outcomes.
• Translate complex statistical findings and model outputs into compelling business narratives for cross-functional partners.
• Work closely with Data Engineering to ensure data quality, reliable instrumentation, and the development of reusable predictive assets like model feature stores.
• Provide technical guidance to peers and stakeholders on best practices for data exploration, ML modeling, and causal methodologies.