Staff Data Scientist, Growth Analytics
New
United StatesFull-TimeStaff
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 8+ years
- Required Skills
- PythonSQLProduct AnalyticsData modelingA/B testingdbt
Requirements
- 8+ years of experience in data science, analytics, or experimentation roles focused on growth, acquisition, or lifecycle analytics.
- Deep expertise in experimentation design and causal inference, including A/B testing, quasi-experimental methods, and geo-based analysis.
- Strong background in attribution modeling, including multi-touch attribution and lifecycle measurement frameworks.
- Expert-level SQL skills and strong Python proficiency for statistical modeling and data analysis.
- Hands-on experience building and owning dbt models, including data marts, testing, documentation, and semantic layers.
- Experience with product analytics and experimentation tools such as Statsig, Amplitude, Mixpanel, or similar platforms.
- Strong understanding of lifecycle marketing tools such as Customer.io, Braze, or Iterable.
- Experience with BI tooling and context engineering for self-service analytics in platforms such as Omni or equivalent.
- Proven ability to translate complex analytical results into clear, executive-level recommendations.
- Bachelor’s degree in a quantitative field; Master’s degree preferred.
Responsibilities
- Own the end-to-end analytical strategy across the marketing funnel, from acquisition and lead generation through visit completion and re-engagement across multiple channels.
- Lead product analytics for onboarding, signup conversion, and early member engagement through the first completed appointment.
- Serve as the executive-facing owner of growth performance, translating funnel trends into actionable insights and strategic recommendations.
- Design and lead experimentation and causal inference programs across both marketing and product domains, ensuring statistical rigor and business impact.
- Own and evolve attribution frameworks, including multi-touch attribution and lifecycle modeling to support investment decisions.
- Build and maintain dbt data models across marketing and product domains, ensuring high-quality, well-documented, and testable data foundations.
- Develop and improve product and event instrumentation, including implementation and optimization of experimentation tools and tracking systems.
- Engineer semantic layers and BI context to enable reliable self-service analytics and AI-assisted insights for stakeholders.
- Partner closely with growth, product, and marketing leadership to embed analytics into decision-making processes.
- Drive clear, executive-ready narratives that explain performance shifts and identify actionable growth levers.
View Full Description & ApplyYou'll be redirected to the employer's site
