Senior Data Scientist, CX Analytics

About the role

This role focuses on advancing customer experience analytics through sophisticated data science. The successful candidate will take ownership of revenue calibration models, translating support interactions into quantifiable revenue signals. A key responsibility involves designing and executing causal inference frameworks to measure the impact of various CX programs on customer retention and product engagement.

The position requires building and maintaining LLM-powered classification pipelines for tasks like contact taxonomy and friction detection. This involves close collaboration with Analytics Engineers to integrate models into the CX data infrastructure. Additionally, the Senior Data Scientist will partner with CX Program Managers and Product teams to develop segmentation models and behavioral signals that drive personalized customer experiences and improve business outcomes.

Success in this role means consistently upholding a high standard for statistical rigor across all CX analytics. This includes ensuring that experimental designs, causal analyses, and model outputs meet the necessary quality for executive reporting and regulatory compliance. The work aims to provide clear, actionable insights from complex model outputs to both executive and product audiences.

The annual base salary for this position ranges from $180,370 to $212,000 USD, with total compensation potentially including equity and bonus eligibility.

Skills that matter here

• Statistics: This role requires maintaining a high bar for statistical rigor in experimentation, causal analyses, and model outputs.
• Mathematics: A strong mathematical foundation is essential for building and evolving revenue calibration models and designing causal inference frameworks.
• A/B testing: Practical expertise in A/B testing is needed to design and execute experiments measuring the impact of CX programs.
• causal inference: The role involves designing and executing causal inference frameworks to quantify the incremental impact of CX initiatives.
• ML: Expertise in machine learning is applied to ambiguous business problems and for building LLM-powered classification pipelines.
• NLP: Experience in designing and deploying NLP pipelines, specifically LLM-based classification, is required for customer friction detection and issue attribution.

Who this role suits

• Someone with a quantitative academic background (Statistics, Mathematics, Computer Science, Economics) and at least five years of relevant professional experience, or three years with a PhD.
• An individual who has demonstrated experience building revenue attribution or causal impact models in consumer-facing or operational analytics.
• A person capable of synthesizing complex model outputs into clear, actionable narratives to influence cross-functional stakeholders.
• Someone who thrives in tackling ambiguous problem spaces with limited prior art, driving impactful data science projects independently.

From the employer

What you'll do

• 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.

Required Skills and Experience

• 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.

Pay Transparency Notice

• Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). Annual base salary range (excluding equity and bonus): $180,370—$212,000 USD.
• Application Limit: Candidates may submit a maximum of 4 applications per 30-day period.
• Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws.
• US Applicants: View [Employee Rights](https://www.dol.gov/sites/dolgov/files/WHD/legacy/files/eppac.pdf), [Know Your Rights](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12.pdf), and [E-Verify](https://static-assets.coinbase.com/e-verify.pdf) Notice of Participation.
• Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at [email protected]. Need screen reading technology? [Click here](https://chromewebstore.google.com/detail/screen-reader/kgejglhpjiefppelpmljglcjbhoiplfn) to download a free compatible screen reader and view the [tutorial](http://www.chromevox.com/tutorial/).
• Data Privacy & Arbitration: By submitting your application, you agree to our [Candidate Privacy Notice](https://www.coinbase.com/legal/applicant_privacy_notice). US applicants: By submitting your application, you agree to [Arbitration of Disputes](https://www.coinbase.com/legal/application-arbitration-agreement).
• AI Disclosure: Coinbase is piloting an AI tool based on machine learning technologies to conduct initial screening interviews to qualified applicants. The tool simulates realistic interview scenarios and engages in dynamic conversation. Coinbase is also piloting an AI interview intelligence platform to transcribe and summarize interview notes, allowing our interviewers to fully focus on you as the candidate. Coinbase will not use AI to make decisions impacting employment.