Senior Data Scientist, CX Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership and enhance CX's Downstream Impact of Support (DSI) revenue calibration models, converting support interaction data into measurable revenue indicators.

• Create and implement causal inference frameworks and experiments to assess the additional impact of CX programs (such as Concierge, Proactive Outreach, and automation interventions) on customer retention and product engagement.

• Develop and sustain LLM-driven classification pipelines for CX contact taxonomy, customer friction detection, and issue attribution, collaborating with Analytics Engineers to integrate models into CX's regulated Source of Truth infrastructure.

• Collaborate with CX Program Managers and Product teams to establish segmentation models and behavioral signals that foster personalized experiences and enhance business outcomes.

• Uphold a high standard of statistical rigor within CX's analytics function, guaranteeing that experimentation, causal analyses, and model outputs meet the criteria necessary for executive reporting and regulatory compliance.

⛳️ Requirements

• A BA/BS in a quantitative discipline (such as Statistics, Mathematics, Computer Science, or Economics) with over 5 years of relevant experience, or a PhD in a quantitative field with more than 3 years of relevant experience.

• Proven experience in developing revenue attribution or causal impact models within a consumer-facing or operational analytics environment.

• Practical knowledge of applying statistical concepts, including A/B testing, causal inference, and machine learning, to complex real-world business challenges.

• Experience in designing and implementing LLM-based classification or NLP pipelines, emphasizing production-level accuracy and evaluation rigor.

• Capacity to influence cross-functional stakeholders by distilling complex model outputs into clear, actionable narratives for executive and product audiences.

• Demonstrated track record of leading impactful data science projects that address ambiguous problem areas with limited prior frameworks.

• Employs generative AI in a responsible manner, ensuring human oversight to produce business-ready outputs and achieve measurable enhancements in workflow efficiency, cost, and quality.

• Shows proficiency in responsibly utilizing generative AI tools and copilots (such as LibreChat, Gemini, Glean) in everyday tasks, continuously adapting as tools evolve, and applying human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.

🏝️ Benefits

• Eligibility for equity and bonuses

• Comprehensive medical benefits

• Dental coverage

• Vision coverage

• 401(k) plan