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Airbnb

Data Scientist, Operations Research/Customer Support (ML/Algo)

Sorry, this job was removed at 04:22 p.m. (PST) on Tuesday, Jun 03, 2025
Remote
Hiring Remotely in United States
148K-174K Annually
Remote
Hiring Remotely in United States
148K-174K Annually

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Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 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:

Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. Customer Support (CS) aims to build the world’s most loyal travel community through exceptional service. Personalizing our CS offerings will allow us to meet our customers when and how they need us most.

As a Data Scientist working on Algorithms 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.

The Difference You Will Make:

For this role, we’re seeking a candidate with NLP/LLM proficiency 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 x AI space by designing scalable scientific solutions for problems like:

  • Understanding and improving the performance of our AI Agent.
  • Scaling the high-quality synthetic datasets curation across various CS domains for training and evaluating LLM.
  • Implementing advanced methods to automate the LLM evaluation process with high efficiency and quality.
  • Generating most helpful self-solve contents in line with Airbnb policy leveraging generative AI to automate low-complexity issues.

A Typical Day: 

  • Identify high impact business opportunities through data exploration and model prototype, translate business problems into scientific formulations.
  • Work collaboratively with cross functional partners including software engineers, product managers, operations and research, to refine requirements for LLMs, drive scientific decisions, and quantify impact.
  • Hands-on develop, productionize, and operate machine learning models and pipelines at scale, including both batch and real-time use cases, structured and unstructured data.
  • Build scalable performance measurement solutions for LLMs evaluation with internal paved path tooling, incorporating industry best practice and state-of-the-art innovations.

Your Expertise:

  • 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 and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse.
  • Deep understanding of machine learning lifecycle best practices (e.g. training/serving, feature engineering, feature/model selection, labeling, A/B test), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, personalization and recommendation).
  • Proficiency with LLMs and/or related AI, NLP, CV, UGC/content understanding topics including deep learning, information retrieval, or knowledge extraction. For example, BERT, GPT-2/3/4, LLaMA, Mistral.
  • Proven ability to communicate clearly and effectively to audiences of varying technical levels, observation causal inference skill is a plus.
  • 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.

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. 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: [email protected]. 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.  

Pay Range
$148,000$174,000 USD
HQ

Airbnb San Francisco, California, USA Office

888 Brannan Street, San Francisco, CA, United States, 94103

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