Staff Data Scientist - Inference, Experimentation

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 billion guest arrivals in almost every country across the globe. Every day, Hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

The mission of the Core Data Science team is to ensure that we are leveraging state-of-the-art science at Airbnb for the highest possible impact on the business and the community. We do that by building reusable tools and models that empower DS teams across the organization and by tackling the most technically challenging, high-impact data science problems the company faces.

The Difference You Will Make: 

As a Staff Data Scientist working on experimentation and causal inference, you will be partnering closely with the engineering team that owns the experimentation platform to develop the next generation of methods and tooling for Airbnb's unique causal measurement challenges. You will also work closely with Data Practitioners across the company to share best practices and to identify opportunities to improve the experimentation platform.

The keys to success in this role are effective partnerships with engineers and data scientists, a problem-solving mindset, and the ability to connect business/product needs to appropriate technical solutions. Effective experimentation is fundamental to product development and optimization at Airbnb, and this role will be a significant part of its future.

A Typical Day:

• Building out Bayesian inference
• Bias correction for marketplace experiments with strong interactions
• Developing surrogate metrics for faster and more accurate experimentation
• Accelerating the iteration cycle for online testing of ML/AI models
• Developing methods and tools for continuous testing and optimization (e.g. bandits)

Your Expertise:

• Advanced degree in a quantitative field, e.g. Operations Research, Economics, Mathematics, Physics
• Proven ability to design analytical solutions to complex problems with real world applications
• 6+ years (with Ph.D) or 8+ yrs of experience of working or doing research in one or more experimentation / causal inference domains
• Strong programming (R, Python / Scala / Java / C++ or equivalent) skills
• Versatility to communicate clearly with both technical and non-technical audiences.
• Publications or presentations in recognized Data Science journals/conferences is a plus. 

Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.