Data Scientist, Airbnb
Operations Research/Customer Support, Inference
$148-174k
More information about location
Community marketplace for holiday accomodation
Be an early applicant
Community marketplace for holiday accomodation
1001+ employees
Be an early applicant
$148-174k
More information about location
1001+ employees
Company mission
To create a world where anyone can belong anywhere.
Role
Who you are
- 2+ years of relevant industry experience (e.g. ML scientist, tech lead, junior faculty) and a Master’s degree or PhD in relevant fields
- Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
- Experience with causal inference and experimentation techniques, ideally in a multi-sided platform setting
- Proven ability to communicate clearly and effectively to audiences of varying technical levels
- Proven mix of strong intellectual curiosity with high level of pragmatism and engagement with the technical community. Publications or presentations in recognized journals/conferences is a plus
- Ability to take a product-oriented mindset in using conceptual and innovative thinking to develop and apply solutions taking into consideration the user experience
What the job involves
- As a Data Scientist working on Inference in CS, you will have the opportunity to collaborate with a strong team of engineers, product managers, designers and operation agents to build scalable and robust systems to match our services to specific customer needs
- You will be able to create meaningful impact through deep scientific understanding and by designing interventions for Airbnb CS’s most critical challenges
- For this role, we’re seeking a Causal Inference/Operations Research expert to join the Customer Support Data Science team. You will work closely with the tech lead for this area on significant components of larger projects and have a direct opportunity to contribute and influence in the CS Personalization space by designing scalable scientific solutions for problems like:
- Creating causal models to identify segments of users with unique CS needs and develop algorithms to match users with the appropriate CS path
- Determine allocation strategy of Make Goods budget to maximize business impact
- Estimating the long term impact of changes in the CS experience for targeted user groups
- Providing strategic insights on tradeoffs between CS quality and cost to empower us to offer the best possible CS experience to our customers
- Optimizing CS routing engines with advanced algorithms and developing simulations to validate them
- Building a deep understanding of our individual agent’s abilities to improve CS quality
- Measuring the CS personalization products through rigorous experimentations and driving data-informed launch decisions
- Build segmentation models for various CS scenarios including data exploration, optimization and model prototyping
- Work collaboratively with cross functional partners including software engineers, product managers, operations and research, to refine requirements for segmentation models, drive scientific decisions, and quantify impact
- Develop strategies to match users with the appropriate CS solutions
- Design and implement quasi-experiment frameworks to measure feature launch effectiveness when A/B testing is not feasible
- Integrate causal modeling with ML models in order to improve performance of model-derived interventions
- Regularly present work internally at monthly meetings to technical, engineering and product stakeholders to iterate and generate excitement on roadmap progress
- Bring new ideas to the team which can improve the operational efficiency of customer support at Airbnb
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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