Senior Staff Data Scientist -- Relevance Measurement Science and Engineering

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. It takes a unified team committed to our core values to achieve this goal. Airbnb's various functions embody the company's innovative spirit and our fast-moving team is committed to leading as a 21st century company.

The Relevance and Personalization team at Airbnb is responsible for search and personalization across the entire Airbnb digital platform. Be a leader in the team working on critical, impactful projects with focus on search ranking, recommendations, autocomplete, query understanding and Airbnb’s ranking platform. We collaborate closely with teams across Airbnb to customize the guest search experience and support a healthy marketplace for hosts and guests to further Airbnb’s mission of creating a world where people can Belong Anywhere.

Measurement science is a key part of product development and data-informed decision-making at Airbnb. The Relevance and Personalization team relies on various cutting edge measurement methods, from offline evaluation, to agile online exploration and large scale online randomized experiments, for every step of decision making.

This role aims to maximize the efficiency of measurement methodologies, practices and data science infrastructure. We are looking for a Senior Staff Data Scientist who can uplevel how we iterate, evaluate and evolve relevance and personalization machine learning models and applications, as well as the data science infrastructure to accelerate applied research and empower a greater data science community at Airbnb.

Responsibilities:

• Innovate and improve the whole offline to online evaluation flow for a large scale ML product like search ranking algorithms, including but not limited to, information retrieval offline evaluation, interleaving, reinforcement learning and online experimentation.
• Research and engineer new signals and design metrics to speed up decision making.
• Tackle causal inference challenges related to two sided marketplace and interference.
• Develop data science solutions into high quality, modulated and reusable components. Build data science infrastructure to serve and empower a greater data science community. 
• Assess return and risk under uncertainty.
• Communicate clearly and effectively to cross functional partners of varying technical levels and drive impact

Qualifications:

• 8+ years of industry experience and an advanced degree in statistics, mathematics, computer science, economics, computational social science and related fields, and strong engineering knowledge. 
• Significant industry experience in measurement, online and offline evaluations and causal inference.
• Passionate about applied research connecting state-of-art methodology with real world applications, through hands-on work creating packages, toolings and data products to connect science to production.
• Proficient in Python or R, as well as query languages such as SQL, Hive or Presto. Web scale data analysis and engineering experience is a plus. 
• Experience working on production code, strong understanding of engineering systems and web applications, and full stack experience is a plus.
• Publication in areas of machine learning and statistical methods is a plus.

The starting base pay for this role is between $210,000 and $260,000. The actual base pay is dependent upon many factors, such as: education, experience, and skills. 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.