Data Science TLM Manager - Search and Personalization
at Airbnb
š United States
$192,000-243,000 per year
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
Statistics @ 4 Algorithms @ 4 Machine Learning @ 7 Data Science @ 4 Leadership @ 4 Communication @ 4 Mentoring @ 4 Technical Leadership @ 4Details
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:
At Airbnb, our mission is to create a world where anyone can belong anywhere. As we continue to grow and innovate, our search and personalization strategies play a critical role in enhancing the guest and host experience. We are looking for a passionate and talented Data Science TLM (Tech Lead Manager) Manager to join our team and drive the future of search and personalization.
The Difference You Will Make:
As a Data Science TLM Manager in the Search and Personalization space, you will have a unique opportunity to shape Airbnb's search and personalization strategy. You will serve as the active point of contact between the relevance team and the product organization, ensuring that our models and algorithms are both high-quality and aligned with our product vision. Your role will involve developing specialized models to power our recommendation platform, partnering with product and relevance teams, and understanding the impact of model changes on the overall product experience. You will also lead and mentor a team of talented individual contributors (ICs), driving innovation and excellence in search and personalization.
A Typical Day:
- Lead and mentor a team of data scientists, guiding them through modeling and inference tasks.
- Develop and refine Airbnb's search and personalization strategy in collaboration with cross-functional teams.
- Ensure the quality and effectiveness of specialized models powering our recommendation platform.
- Act as the liaison between the relevance team and the product organization, facilitating effective communication and collaboration.
- Understand and evaluate the implications of model changes on the user experience, ensuring optimal outcomes.
- Partner with product and relevance teams to align on goals and deliverables.
- Drive the development of innovative personalization strategies to enhance user engagement and satisfaction.
Your Expertise:
- Advanced degree (PhD or Master) in Computer Science, Data Science, Statistics, or a related field.
- 7+ years of relevant industry experience, with a focus on search and personalization.
- Proven experience in a technical leadership role within data science, particularly in the relevance ranking space.
- Strong technical skills with the ability to dive into the details of modeling and inference tasks.
- Experience managing and mentoring a team of individual contributors (ICs).
- Deep understanding of machine learning, recommendation systems, and data-driven product development.
- Excellent communication and collaboration skills, with the ability to work effectively across teams and stakeholders.
- Strategic thinker with a passion for innovation and problem-solving.
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.
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.
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.