Data Quality Analyst, AirDNA

• We welcome applicants from all backgrounds and encourage you to apply even if you don’t check every box. Passion, potential, and perspective matter here
• 1+ years of professional experience working with data, with a focus on software development and advanced analytics
• Full proficiency in English both verbally and written
• Proficiency working with SQL and Python (pandas, datetime, numpy, dictionaries, packages)
• Experience working with large data sets in distributed systems such as Snowflake
• Excellent communication skills, data driven, critical thinker and attention to detail
• Flexibility, time management and a learning mindset
• Data driven, critical thinker and hungry to learn
• Comfortable working with data validation, models, and architecture

Desirable

• As a data quality analyst, you will work with product, other data scientists and engineering to help bring innovative solutions to market. At AirDNA, models are at the heart of all of our products
• The data quality analyst is responsible for helping set strategies to continuously improve our data accuracy to help our customers stay ahead in a fast-changing industry
• We help people make smarter data-driven decisions based on our short-term rental data and we will continuously strive to expand and improve that data while looking to maximize the value it provides
• We develop solutions to facilitate customers gaining access and value from our data
• Conduct exploratory data analysis on short-term rental pricing and occupancy datasets to identify patterns, trends, and outliers
• Collaborate with domain experts to gain a deep understanding of factors influencing pricing and occupancy dynamics in the short-term rental market
• Analyze predictive models to predict short-term rental markets behavior
• Collaborate with data engineering teams to integrate new data sources and ensure data quality for modeling purposes
• Work closely with cross-functional teams, including product managers, engineers, and business analysts, to implement pricing strategies based on data-driven insights
• Clearly communicate findings and recommendations to both technical and non-technical stakeholders
• Implement monitoring systems to track model performance over time and proactively identify issues or deviations
• Regularly analyze models to adapt to changes in market conditions and business requirements

• First stage: Virtual interview with the People Team at AirDNA (Online-30min)
• Second stage: Meet the Hiring Manager (Online-45min)
• Final stage: Technical Review + Peer Meet (1.5hrs)
• Ideal start date: May 2025