Data Scientist
Core
Partner with GTM teams to design experiments, build predictive models for churn/retention, and turn ambiguous business questions into actionable insights.
Role type
Mid-level applied data scientist (GTM analytics)
Builds
Predictive models (churn, LTV, lead scoring), measurement frameworks, and analytics infrastructure
Domain
B2B SaaS, Customer Success, Go-to-Market
Deliverable
production ML models | dashboards & analysis
Required skills
Python, SQL, causal inference, A/B testing, predictive modeling, data visualization, stakeholder partnership
Preferred skills
B2B SaaS domain, ML Ops tools (Snowflake, Databricks), orchestration tools (Airflow), early-stage team experience
Technologies
Python, SQL, Snowflake, pandas, scikit-learn, statsmodels, matplotlib, seaborn, plotly, Streamlit, Tableau, Looker, Airflow, Orchestra
Responsibilities
Design and analyze A/B tests and causal-inference methods; build and maintain predictive models for customer health and expansion; define metrics and partner with BI/Data Engineering teams; explore open-ended questions to identify drivers of key business metrics.
Seniority
Mid-level, hands-on IC
