Senior Data Scientist, CX Analytics

Coinbase

Senior Data Scientist on the CX Consumer Analytics team at Coinbase. Owns revenue models and transforms data into insights for customer support interactions.

Posted 6/16/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $180,370 - $212,000 per yearWebsite

About the role

Key responsibilities & impact

Own and evolve CX's Downstream Impact of Support (DSI) revenue calibration models, translating support interaction data into quantified revenue signals.
Design and execute causal inference frameworks and experiments to measure the incremental impact of CX programs (Concierge, Proactive Outreach, automation interventions) on customer retention and product engagement.
Build and maintain LLM-powered classification pipelines for CX contact taxonomy, customer friction detection, and issue attribution, partnering with Analytics Engineers to productionize models into CX's governed Source of Truth infrastructure.
Partner with CX Program Managers and Product teams to define segmentation models and behavioral signals that enable personalized experiences and improve business outcomes.
Maintain a high bar for statistical rigor across CX's analytics function, ensuring experimentation, causal analyses, and model outputs meet the standards required for executive reporting and regulatory defensibility.

Requirements

What you’ll need

A BA/BS in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) with 5+ years of relevant experience, or a PhD in a quantitative field with 3+ years of relevant experience.
Demonstrated experience building revenue attribution or causal impact models in a consumer-facing or operational analytics context.
Practical expertise applying statistical concepts including A/B testing, causal inference, and ML to ambiguous, real-world business problems.
Experience designing and deploying LLM-based classification or NLP pipelines with a focus on production-grade accuracy and evaluation rigor.
Ability to influence cross-functional stakeholders by synthesizing complex model outputs into clear, actionable narratives for executive and product audiences.
Demonstrated experience driving impactful data science projects that tackle ambiguous problem spaces with limited prior art.
Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality.

Benefits

Comp & perks

Equity and bonus eligibility
Medical benefits
Dental benefits
Vision benefits
401(k)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

revenue calibration modelscausal inference frameworksA/B testingmachine learningclassification pipelinesNLPstatistical rigordata science projectsquantitative analysiscustomer retention

Soft Skills

influencing stakeholderssynthesizing complex informationclear communicationactionable narrativescross-functional collaborationproblem-solvingadaptabilitycritical thinkingproject managementteamwork