Lead Data Scientist, Customer & Growth Analytics

Role Overview

Design, build, and maintain predictive models that support customer expansion, including propensity-to-upgrade and engagement scoring models. Use behavioral, usage, firmographic, and lifecycle data to identify signals that indicate readiness for AI adoption and expansion. Partner with Lifecycle Marketing to translate model outputs into actionable segments and testable hypotheses across the customer lifecycle.

What You Will Do

Design, build, and maintain predictive models that support customer expansion, including propensity-to-upgrade and engagement scoring models. Use behavioral, usage, firmographic, and lifecycle data to identify signals that indicate readiness for AI adoption and expansion.

Why It Might Be a Fit

Strong proficiency in Python or similar data science tools, including feature engineering and model evaluation. Demonstrated experience working with large, complex datasets such as product usage, behavioral logs, or campaign data. Experience partnering with Marketing, Growth, or Customer Success teams to translate insights into action.

Requirements

• 5+ years of experience in data science, analytics, or applied machine learning in a B2B SaaS or subscription-based environment.
• Experience building predictive or classification models that influence customer growth, retention, or expansion decisions.
• Strong proficiency in Python or similar data science tools, including feature engineering and model evaluation.
• Demonstrated experience working with large, complex datasets such as product usage, behavioral logs, or campaign data.
• Experience partnering with Marketing, Growth, or Customer Success teams to translate insights into action.
• Familiarity with deploying or activating models within analytics platforms or CDPs; experience with Treasure Data or similar platforms is a plus.
• Strong understanding of experimentation, model validation, and measuring impact using both statistical and business metrics.
• Ability to clearly communicate technical concepts and insights to non-technical stakeholders.
• Curiosity and ownership mindset, with a strong bias toward building models that are used and deliver measurable outcomes.

Benefits

• Flexible vacation
• Two company-wide Mental Health Days off
• Access to the Headspace app
• Retirement savings
• Tuition reimbursement
• Employee incentive programs
• Resources for mental, physical, and financial wellbeing

Tagged as: Python