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Data Scientist
Airbnb
San Francisco, CA, United States
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Data Scientist - Airbnb for Work
Airbnb has become a global platform that connects travelers and hosts from over 34,000 cities. Our mission is to enable a world where anyone can belong anywhere, and providing a world class experience to our users is critical to our mission.
Today’s business travelers have a deeper desire for the comforts of home that they leave behind when they are away. As such, business travelers are displaying a huge interest in staying in Airbnbs rather than traditional accommodations.To better enable traveling for work, there are a number of foundational analytics products we need to build for company travel managers, expensing agencies, internal sales teams and individual travelers. To start, we are looking to build analytics for acquisition strategy, sales lead generation ranking models, and user experimentation frameworks.
Working alongside other Data Scientists who dig deep into Airbnb's data, you will translate complex findings and results into a compelling narrative. In this role, you will have tremendous scope to work with engineers, sales & marketing teams, and senior business partners. If you’re passionate about leveraging data to drive business and product decisions, we want to hear from you. The ideal candidate has an eye for detail, great communication, and a keenness for problem solving. Examples of projects you would work on include, but are not limited to:
Responsibilities:
• Investigating challenging questions around user behavior
• Creating business critical dashboards
• Defining key metrics
• Designing and measuring incentive programs for business travelers and companies
Ownership:
• Conceptualize, create, and maintain monitoring dashboards for tracking key metrics
• Review A/B tests to help your team make good product decisions
• Communication: design and draft regular reports of progress towards company goals to product groups and senior stakeholders
• Creativity: refine and improve definition of metrics as the company’s challenges and data evolve
• Engineering: collaborate with data engineers to better log data and manage the timeliness and accessibility of data tables
Investigation:
• Carry out ad hoc descriptive analysis according to product needs, whether it be potential product opportunities or for debugging
Empowerment:
• Strategize & build tools to make analyses easily repeatable and generalizable by other team members in the future
Experience:
• Professional experience in data analysis and visualization
• Confidence with analytical tools such as R, Python, Stata,or Matlab
• Proven ability to succeed in both collaborative and independent work environments
• Expertise designing and delivering presentations
• Also valuable:
• Familiarity with SQL or other querying language
• Experience with a programming language
• Ability to work with dashboarding software such as Tableau or Google Analytics