Staff Analytics Engineer, Trust

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.

About the Team

We are a group of data scientists working on products and analytics to enhance Trust and Safety on Airbnb’s platform. What’s the best way to know that our users are who they say they are? How do we balance fraud prevention and user experience? As a Data Scientist working on Trust, 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 detect, prevent and mitigate fraud on Airbnb. You will be involved in building highly available and real-time risk detection services to understand ever evolving attack vectors and to keep Airbnb a safe and trusted community. We have a strong team of data scientists, our work is highly sought-after, and our impact on the business is tremendous. If you have a proven background in this field and are excited to help build Airbnb’s community, we want to hear from you.

About the Position

Analytics Engineers build the data foundation for reporting, analysis, experimentation, and machine learning at Airbnb. We are looking for someone with expertise in metric development, data modeling, SQL, Python, and large scale distributed data processing frameworks like Presto or Spark. Using these tools, you will transform data from data warehouse tables into valuable data artifacts that power impactful analytic use cases (e.g. metrics, dashboards). You will sit at the intersection of data science and data engineering, and work collaboratively to achieve highly impactful outcomes. Data can transform how a company operates; high data quality and tooling is the biggest lever to achieving that transformation. You will make that happen.

Responsibilities:

• Understand data needs by interfacing with fellow Analytics Engineers, Data Scientists, Data Engineers, and Business Partners
• Architect, build, and launch efficient & reliable new data models and pipelines in partnership with Data Engineering
• Design, define, and implement metrics and dimensions to enable analysis and predictive modeling
• Become a data expert in your business domain and own data quality
• Build tools for auditing, error logging, and validating data tables
• Build and improve data tooling in partnership with internal Data Platform teams 
• Define logging needs in partnership with Data Engineering
• Design and develop dashboards to enable self-serve data consumption

Minimum Qualifications:

• Passion for high data quality and scaling data science work
• 8+ years of relevant industry experience
• Strong skills in SQL and distributed system optimization (e.g. Spark, Presto, Hadoop, Hive)
• Expert in at least one programming language for data analysis (e.g. Python, R)
• Experience in schema design and dimensional data modeling
• Ability to perform basic statistical analysis to inform business decisions
• Proven ability to succeed in both collaborative and independent work environments
• Detail oriented and excited to learn new skills and tools

Preferred Qualifications:

• Experience with an ETL framework like Airflow
• Python, Scala, Superset, and Tableau skills preferred
• An eye for design when it comes to dashboards and visualization tools
• Familiarity with experimentation and machine learning techniques