Tech Stack

Description

In this role, you will serve as a senior analytical leader, driving a data-driven culture and advancing experimentation capabilities. You will partner with Go-to-Market teams, Marketing, Product, and leadership to deliver actionable insights and causal impact analysis, ensuring data-driven decision-making across the organization.

Requirements

• 6+ years in applied data science, economics, or product analytics with proven use of experimentation and causal inference.
• Bachelor’s in Math, Statistics, Economics, Computer Science, or related quantitative field; Master’s preferred.
• Expertise in causal inference methods (PSM, diff-in-diff, instrumental variables) and A/B testing methodologies.
• Advanced proficiency in Python or R for statistical modeling, and expert-level SQL.
• Experience with data warehouses (e.g., Snowflake, Postgres) and pipeline tools (dbt, Airflow, Databricks) is a plus.

Responsibilities

• Lead the experimentation roadmap, focusing on high-leverage business questions like customer workflows, churn risk, and LTV.
• Design and analyze complex A/B tests, multivariate experiments, and apply Bayesian experimentation.
• Apply advanced causal inference techniques (diff-in-diff, synthetic control, PSM, IV) when RCTs are infeasible.
• Conduct deep dive analysis to discover latent user behavior and emerging trends.
• Define and govern a unified KPI framework across product health and business outcomes.