Responsibilities

• Collaborate with Product, Engineering, Marketing, and cross‑functional partners to inform, influence, and execute strategy across product and growth surfaces.
• Build AI‑driven analytics agents that automate workflows such as experimentation readouts, funnel diagnostics, anomaly detection, and business reviews, and partner with Engineering to productionize these systems at scale.
• Develop and maintain experimentation, causal measurement, and product analytics frameworks that support acquisition, activation, engagement, retention, monetization, and LTV.
• Design and implement measurement and modeling approaches across paid, owned, and product surfaces, using uplift modeling, causal inference, and experimentation rigor (MMM optional).
• Develop a deep understanding of complex product and marketing systems to identify opportunities, risks, and levers for growth.
• Communicate insights clearly to technical and non‑technical audiences, influencing product and marketing roadmaps through data, modeling, and AI‑driven insights.

Requirements

• 7+ years in analytics, data science with deep hands‑on execution.
• Strong technical skills in SQL, Python, experimentation, and statistical modeling .
• Experience building AI‑driven analytics workflows (LLMs, agents, automation, or similar).
• Solid background in product and growth analytics across activation, engagement, retention, and monetization.
• Experience with causal inference, uplift modeling, and experimentation frameworks .
• Ability to operate as a high‑leverage IC who partners closely with executives and cross‑functional leaders.
• Excellent communication and storytelling skills for technical and non‑technical audiences.

Preferred

• Experience in fintech, consumer tech, or data‑driven product organizations is a plus.
• Familiarity with modern data stacks (Databricks, Snowflake, dbt, Amplitude, Looker) is a plus

Benefits