Data Analyst, MyHealthTeam

About the role

MyHealthTeam is looking for a motivated Data Analyst to join our Analytics team. Reporting to the Senior Manager of Analytics, you’ll partner with Product, Account Management, and other internal teams to surface insights, evaluate experiments, and inform strategic decision-making. Your work will directly shape product improvements, member engagement, and the overall impact we deliver to our growing community.

What you'll do Develop dashboards, recurring reports, and metrics to track website and product performance Partner with Product Managers to evaluate A/B tests using VWO and our homegrown experimentation framework Define, maintain, and document KPIs to ensure consistency across teams Conduct deep-dive analyses to understand user behavior and identify opportunities for optimization Support the Account Management team with data requests and client-facing insights Serve as a backup resource for analytics implementation and data quality validation (GTM/GA4 event tagging, troubleshooting, issue resolution) Qualifications 2+ years of experience in an analyst role, ideally within web or product analytics Proficiency with SQL for data extraction and transformation Experience with GA4 (or similar analytics platforms) Experience with Google Tag Manager (or another tag management system) (Preferred, not required) Familiarity with clickstream, event-level, or behavioral data sets Foundational understanding of statistical concepts (e.g., distributions, confidence, variance) Strong intellectual curiosity and a proactive approach; able to go beyond the initial question to uncover meaningful insights Excellent attention to detail, especially regarding data accuracy and implementation Experience with BI / visualization tools such as Looker Studio, Tableau, or similar Ability to translate complex analytical concepts into clear, actionable recommendations for non-technical stakeholders Strong written and verbal communication skills Ability to design and evaluate experiments, including considerations for sample size, measurement, and variable dependencies