Senior Data Scientist, Airbnb
Trust, Algorithms
$148-174k
More information about location
Community marketplace for holiday accomodation
Open for applications
Community marketplace for holiday accomodation
1001+ employees
Open for applications
$148-174k
More information about location
1001+ employees
Company mission
To create a world where anyone can belong anywhere.
Role
Who you are
- Advanced degree in a quantitative field. PhD is a plus
- 6+ years of relevant industry and/or academic experience developing scientific frameworks, building machine learning models, and implementing advanced experimentation techniques
- Strong fluency in Python and familiarity with modern frameworks (e.g. Pytorch, Tensorflow) for hands-on IC work and advanced data analysis in SQL at scale
- Deep understanding of modern machine learning techniques and their mathematical underpinnings (e.g. classification, clustering, optimization, deep neural networks and natural language processing). Ability to develop, validate, and deploy new model applications as well as enhancing existing algorithms to achieve improved performance and model explainability
- Comfortable collaborating with software engineers to understand complex systems and abstracted logs
- Proven ability to create and drive technical and impactful roadmaps for the business, and lead seamless execution of it
- Proven ability to communicate clearly and effectively to cross functional partners of varying technical levels
- Experience with advanced experimentation techniques is a plus
- Experience productionizing real-time machine learning models is a plus
What the job involves
- The User Segmentation team is committed to building a golden set of dynamic and static attributes for our guests and hosts, which can drive valuable insights for many product teams at Airbnb
- This is a highly cross-functional effort, spanning Trust, Marketing, Customer Support, Guest & Host, Core, and Quality teams
- In this role, you will develop and implement methodologies to identify essential features that describe Airbnb users by leveraging machine learning models, statistical inference, and AI
- You will collaborate closely with data engineering teams to define and build actionable knowledge about guests, hosts, and listings, ensuring user features are widely accessible and impactful across the business
- Success in this role will be measured by your ability to deliver robust data insights and scalable solutions that drive strategic decision-making and enhance user experiences
- Build machine learning models to detect high-risk activities, develop data mastery to uncover learnings, and formulate structured frameworks to classify and interpret our users’ behavior
- Work cross-functionally with operations and product teams to define and collect labels for model training, optimize the effectiveness of manual review, and build self-satisfiable verifications that scale
- Develop measurement strategies to test new product features that deter and mitigate risk, while adhering to ethical guidelines
- Regularly present work internally to technical, engineering and product stakeholders to iterate and generate excitement on roadmap progress
- Publish externally and engage with the scientific community to advance Airbnb’s standing
- Devise models to make optimal business decisions while minimizing risk
- Utilize Deep Learning techniques for advanced feature engineering and model building, e.g., how to model for user behaviors sequences, or how can we detect anomalies effectively
Our take
When Airbnb was originally founded, the product helped customers book air mattresses on people's apartment floors. Since then, Airbnb has had over a billion customers hosted through its platform. With more than 4 million registered hosts worldwide, it has grown into a major player in the hospitality sector.
Airbnb has been successful in disrupting the traditional holiday lettings sector. Before it existed accommodation was limited to hotels and bed and breakfasts, but Airbnb has mainstreamed the idea of renting out spare rooms or even entire homes. It has created a new sector of hosts purchasing properties to rent out on the platform and provides a level of flexibility and a range of offerings not previously possible for travelers.
Perhaps a victim of its own success, by 2022 supply of Airbnb-listed properties began to outstrip demand in some markets, as hosts overestimated the appetite for domestic travel. However, the company is still posting strong financials and has unveiled new tools to support its hosts in a tougher rental market. With a healthy bottom line and a huge user base, Airbnb is very likely to overcome the current market turbulence and continue its growth.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
25% employee growth in 12 months
Company
Funding (last 2 of 10 rounds)
Apr 2020
$500m
GROWTH EQUITY VC
Mar 2017
$447.8m
SERIES F
Total funding: $3.8bn
Company benefits
- Paid volunteer time
- Health food and snacks
- Generous parental and family leave
- Learning and development
- Annual travel and experiences credit
Company HQ
Showplace Square, San Francisco, CA
Leadership
Brian Chesky
(Co-Founder & CEO)Previously an Industrial Designer, studying at Rhode Island School of Design.
Nathan Blecharczyk
(Co-Founder & CSO)Studied Computer Science at Harvard, and had around 4 years of professional Software Engineering experience before founding Airbnb, including interning at Microsoft.
Joe Gebbia
(Co-Founder)Also studied Industrial Design at Rhode Island, and previously founded various design-related startups
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