Data Analyst, Recruiting

Founded in 2008, Airbnb’s mission is to create a world where people can belong through healthy travel that is local, authentic, diverse, inclusive and sustainable. Airbnb uniquely leverages technology to economically empower millions of people around the world to unlock and monetize their spaces, passions and talents to become hospitality entrepreneurs. Airbnb’s accommodation marketplace provides access to 5+ million unique places to stay in more than 81,000 cities and 191 countries. With Experiences, Airbnb offers unprecedented access to local communities and interests through 15,000 unique, handcrafted activities run by hosts across 1,000+ cities around the world. Airbnb's people-to-people platform benefits all its stakeholders, including hosts, guests, employees and the communities in which it operates. 

We're looking for an experienced Data Analyst to join our global Recruiting organization, and work on the Recruiting Strategy and Operations team. This role will report into the Recruiting Analytics Manager and partner with Recruiting leaders to understand how they currently use data to manage their teams, identify best practices, leverage data and analytics to identify opportunities, and implement new strategies - all with the aim of improving recruiting performance.

If you are passionate about data and want to help empower the recruiting team to ensure a quality candidate experience, educate the organization at large regarding the talent acquisition process and provide critical insights to leadership to guide future talent decisions, then, this is the role for you. If you are a change agent who works deeply to ensure data hygiene, process efficiency and who enjoys developing perspectives using data we’d love to connect with you.

Role & Responsibilities

• Empower leaders and organizations by providing high quality and timely reporting, analyses and actionable insights. 
• Drive deep strategic analysis, drawing insights and transforming data into actionable changes that inform the most important decisions across the organization to improve our understanding of our recruiting organization and its ability to enable us to hire more diverse and high quality talent.
• Partner with our Recruiting Strategy and Operations team to form hypotheses and design programs with end state analysis in mind.
• Design, develop and automate self-service dashboards to ensure our business leadership have easy access to the right information when monitoring organizational health and making talent decisions.
• Develop new models and methods for evaluating existing data or correlating new to existing data sources for intuitive reporting solutions.
• Building out and maintaining the Recruiting Analytics database. This includes contributing to the architecture, and integrating multiple systems and data sources to build large and complex data sets to make them usable for analytics use cases.
• Training and educating client teams on recruiting metrics and dashboards.
• Standing up, socializing, and ensuring consistency around data hierarchy, definitions etc. and maintaining consistent and accurate data in our systems including historical data.
• Utilize strong understanding of business processes, services, and technology to identify opportunities for improvement, simplification, standardization, and automation across our recruiting function.

Requirements

• 2+ years experience in a quantitative analysis role, preferably in Recruiting and/or HR.
• Experience with SQL, other analytics tools, data visualization tools (e.g. Tableau, Google Data Studio), and data pipeline tools (e.g., Airflow).
• Experience managing and working with large databases, data management, including understanding of various data structures and common methods in data transformation, data validation and audit.
• Excellent consulting and collaborative skills – ability to translate business problems into research/analytics studies, as well as ability to communicate the results of analyses with business partners to impact and influence strategy and action at all levels.
• Independence in determining and establishing data analysis priorities to balance ongoing projects with requests from multiple team members.
• Biased toward action, simplifier, and great communicator  - constantly pushing toward clarity and delivery.
• Ability to identify the root causes of changes in key metrics and run tests to validate your hypotheses.

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