Data Scientist, Analytics Engineer

Job Title:  Data Scientist, Analytics Engineer  Job Location: San Francisco, CA Job Openings: 1 Job Posting Date:  Mar 29, 2021 Eligible for Relocation: Yes, this role is eligible for relocation and immigration assessment

Airbnb is one of the world’s largest marketplaces for unique, authentic places to stay and things to do, offering over 7 million accommodations and 40,000 handcrafted activities, all powered by local hosts. An economic empowerment engine, Airbnb has helped millions of hospitality entrepreneurs monetize their spaces and their passions while keeping the financial benefits of tourism in their own communities. With more than half a billion guest arrivals to date, and accessible in 62 languages across 220 countries and regions, Airbnb promotes people-to-people connection, community and trust around the world.

 

About the team

We are looking for talented Data Scientists, Analytics Engineers to join the Guest Experience team. The team is responsible for the end to end guest experience on Airbnb,from the landing pages such as the homepage, the search and listing pages, the signup and booking flow and the actual pre and on-trip experience. The Data Science team works closely with product and engineering to power the guest side data ecosystem, enable easy insights, reliable measurement and influence product development.

Areas of responsibilities

 

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.

Your Responsibilities:

• Understand data needs by interfacing with fellow 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
• Define logging needs in partnership with Data Engineering
• Design and develop dashboards to enable self-serve data consumption

 

Required qualifications

• Passion for high data quality and scaling data science work
• 4+ 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
• Understanding of basic client side data behavior (get/post, polling, api lifecycle, redux store, etc)

 

Benefits

• Stock
• $2,000 yearly employee travel coupon
• Competitive salary
• Paid time off
• Medical, dental, & vision insurance
• Life & disability coverage
• 401K
• Flexible Spending Accounts
• Apple equipment

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status