Lead, Advanced Analytics, Community Support
Leads advanced analytics for Customer Support, partnering with product and operations leaders to improve community and agent experiences through metrics, experimentation, causal inference, and scalable data tools. Requires 8+ years of business analytics experience and strong SQL plus Python or R expertise.
About the job
Responsibilities
- Act as a data thought partner to product and business leaders across Customer Support, providing insights, recommendations, and data-informed decisions.
- Drive day-to-day analytics and create scalable data tools.
- Identify pain points in customer support operations and work with product leadership to improve guest, host, and agent experiences.
- Build and grow measurement capacity using machine learning infrastructure and data science tools.
- Collaborate with engineers, product managers, designers, and operations agents on cross-functional goals related to community safety and trust.
- Lead data-driven roadmaps for Customer Support working groups and recommend actionable, metrics-backed solutions.
- Build business insights and reporting platforms to evaluate behaviors, product interfaces, and processes across the Customer Support platform and contact center network.
- Perform data modeling of entities and use tools and frameworks to optimize community and agent experiences.
- Define and evaluate key metrics, including measurement of new product launches, and communicate the factors driving those metrics.
- Influence data-driven decisions through business reviews, scorecards, self-service portals, OKRs, and planning.
- Influence experimentation and measurement strategies; conduct power analyses, define exit criteria, and apply statistical models to improve inference.
Requirements
- 8+ years of industry experience in business analytics.
- Degree in a quantitative field such as Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, or Operations Research.
- Experience supporting customer service or working closely with operations teams.
- Expert SQL skills and expertise in at least one programming language for data analysis, such as Python or R.
- Experience with non-experimental causal inference, experimentation, and machine learning techniques, ideally in a multi-sided platform setting.
- Working knowledge of schema design and high-dimensional data modeling.
- Ability to work effectively amid ambiguity in a fast-growth, complex environment with minimal direction.
- Ability to identify issues, propose solutions, influence stakeholders, and prioritize what matters most based on data and insights.
Nice to Have
- Master's degree or PhD in a quantitative field.
- Experience with ETL frameworks such as Airflow.
Compensation and Benefits
- Base pay range: $164,000–$191,000 USD.
- May be eligible for bonus, equity, benefits, and Employee Travel Credits.
Skills
SQL, Python, R, Causal Inference, Experimentation, Machine Learning, Statistical Modeling, Power Analysis, Data Modeling, Schema Design, ETL, Airflow, Metrics Definition, Data Analysis
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