Staff, Advanced Analytics, Community Support & Aircover
at Airbnb
USD 176,000-220,000 per year
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
Python @ 4 SQL @ 4 A/B Testing @ 4 R @ 4 Statistics @ 4 ETL @ 3 Airflow @ 3 Machine Learning @ 4 Data Science @ 4 Leadership @ 4 Communication @ 4 Mathematics @ 4 Data Analysis @ 4 Experimentation @ 6 Reporting @ 4Details
Airbnb is seeking an Advanced Analytics Lead to enable travel for millions of guests and hosts by supporting Product and Business leaders within the Community Support (CS) organization. This role leverages Airbnb’s data, machine learning infrastructure, and central data science tools to build measurement capacity, drive analytics roadmaps, and collaborate cross-functionally with engineers, product managers, designers, and operations agents to improve guest, host, and agent experiences.
Responsibilities
- Act as a data thought partner to product and business leaders across CS by providing insights, recommendations, and enabling data-informed decisions.
- Drive day-to-day analytics and create scalable data tools and reporting platforms (scorecards, business reviews, self-serve portals) to measure and improve efficacy and efficiency across CS platform and contact center network.
- Lead and drive data-driven roadmaps for CS working groups; recommend actionable solutions backed by data and metrics and communicate effectively with Product, Operations & Engineering managers of varying technical levels.
- Build business insights & reporting platforms to detect and support behaviors, product interfaces, and processes impacting community and agent experiences.
- Perform data modeling of various entities and use tools & frameworks for optimizing community and agent experiences; work with schema design and high-dimensional data modeling.
- Define and evaluate key metrics, including measurement of ML models that drive product development; communicate what moves these metrics and why.
- Influence experimentation & measurement strategies: conduct power analyses, define exit criteria, and use statistical models to improve inference and causal understanding.
- Identify pain points in traveling and hosting and partner with product leadership to improve experiences for guests, hosts, and agents.
Requirements
- Minimum of 10+ years of industry experience in business analytics. A Masters or PhD in a quantitative field (Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research) is a plus.
- Experience supporting community support and/or working closely with operations teams.
- Expert skills in SQL.
- Expert in at least one programming language for data analysis (Python or R).
- Experience with non-experimental causal inference methods, experimentation (A/B testing) and machine learning techniques, ideally in a multi-sided platform setting.
- Working knowledge of schema design and high-dimensional data modeling; familiarity with ETL frameworks such as Airflow.
- Strong statistical modeling skills; ability to conduct power analyses and establish robust experimentation and measurement strategies.
- Excellent communication and storytelling skills to translate complex data and insights into narratives and actionable recommendations.
- Ability to work under ambiguity in a fast-growth, complex environment and to operate with minimal supervision.
Location & Office Policy
- This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager. Candidates must live in a state where Airbnb, Inc. has a registered entity.
Compensation & Benefits
- Base pay range: $176,000—$220,000 USD (base pay depends on factors such as experience, skills, business needs). This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
Inclusion & Accessibility
- Airbnb is committed to inclusion and belonging and encourages applicants from diverse backgrounds. Candidates with disabilities who require reasonable accommodation for the application or interview process are asked to contact [email protected] with their full name, the role, and the accommodation needed.