Staff Data Scientist - Algorithms/Marketing Technology

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 Marketing Technology focuses on building the best-in-class platform and measurement capabilities to enable marketing and merchandising at Airbnb. We build products that are used by our stakeholders across the company including Marketing (Brand and Performance), Guest Experience, Host, Policy, and more. Our Mission is to enable marketing and product teams to effectively deliver highly personalized and relevant marketing campaigns to the Airbnb community, both on-site and off-site.

The Difference You Will Make:

As one of the most senior Machine Learning Scientists on the team, you will be hands-on in building blue-sky prototypes of data products to pursue opportunities for optimizing and personalizing marketing to engage with Guests and Hosts throughout their journeys with Airbnb. Our team works on interesting problems across a diverse collection of Airbnb’s largest datasets. We are committed to applying innovation and creativity towards extracting a foundational understanding of our user, amidst the richness and heterogeneity of their complex behaviors and preferences. Projects will leverage AI, LLM, and recommendation algorithm to inform personalizing marketing campaigns and to develop future-proofing marketing strategies on generative AI. 

• Extract signals from large-scale structured, unstructured, and user journey data to generate ML-driven insights for improving the efficiency and performances of Airbnb marketing. 
• Demonstrate good judgment in selecting and evaluating methods and techniques for obtaining solutions. 
• Design, run, and diagnose experiments to validate hypotheses and performance of data prototypes 
• Design systems that optimize the marketing engagement with users. 
• Work closely with ML Engineering team as a science partner on technical projects to understand user preferences
• Build data products, model, and identify user intent at various stages of the user product journey
• Research, present, and publish internally and externally, to engage and advance Airbnb’s standing in the scientific community.

A Typical Day:

• Focus time – To build machine learning prototypes, develop data mastery to uncover learnings, and formulate structured frameworks to classify our users’ online product experience and interpret their behaviors
• Autonomy – To apply and investigate state-of-the-art innovations to uplevel Airbnb status-quo approaches to technical problems
• Influence – Clearly scope the technical solutions, milestones of long term innovative projects and align with stakeholders for adoption. 
• Regularly present work internally at monthly meetings to technical, engineering and product stakeholders to iterate and generate excitement on roadmap progress
• Mentorship – Provide technical guidance to junior team members and be accountable for the project outcome. 
• Publish externally and engage with the scientific community to advance Airbnb’s standing

Your Expertise:

• 9+ years of relevant industry experience (e.g. ML scientist, tech lead, junior faculty) and a Master’s degree or PhD in a quantitative field
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization).
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Strong fluency in Python or R for hands-on IC work and advanced data analysis in SQL at scale
• Comfort to collaborate with software engineers to understand complex systems and abstracted logs
• 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, that demonstrates an eagerness to learn and share.
• Knowledge of experimentation and statistical biases. Familiarity with multi-sided marketplaces.
• Nice to have: Hands on experience with large language models, i.e. BERT, LaMDA, GPT-2/3/4, LLaMa. 

Your 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. This role leans toward West coast hours. 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.