Data Analyst

ABA Rank is an independent directory and ranked index covering Applied Behavior Analysis (ABA) clinics, software vendors, and service providers across the United States. Rankings are driven by disclosed data signals rather than editorial picks or paid placement, and the platform surfaces that data through public listings, a matching desk for buyers, and structured feeds for AI assistants. We're hiring a Data Analyst to help turn the index's underlying data - reviews, profile completeness, verification recency, category fit, and traffic patterns - into clear insights that inform how rankings, matching, and product decisions are made.

What you'll do

• Build and maintain reports and dashboards tracking index health, ranking distributions, listing growth, and user engagement across the directory
• Analyze data feeding the four-signal ranking methodology (qualified reviews, profile completeness, verification recency, category fit) to identify trends and anomalies
• Partner with product and engineering teams to define metrics for new features like the matching desk and AI visibility tools
• Query and clean data from internal databases and third-party sources to support recurring and ad hoc analysis requests
• Monitor data quality across the nightly index recompute process and flag inconsistencies or errors
• Present findings and recommendations to stakeholders in a clear, actionable format

What we're looking for

• 2+ years of experience in a data analyst or similar analytical role
• Strong SQL skills and experience working with relational databases
• Proficiency with a data visualization tool such as Tableau, Looker, or Power BI
• Comfort working with spreadsheets and at least one scripting language (Python or R preferred) for data manipulation
• Ability to translate ambiguous business questions into structured analysis and clear recommendations
• Strong attention to detail, especially when validating data used in public-facing rankings

Nice to have

• Experience working with marketplace, directory, or ranking/recommendation systems
• Familiarity with web analytics tools (e.g., Google Analytics) or API-based data sources
• Exposure to A/B testing or experimentation frameworks