Product Data Analyst Contractor

Key Responsibilities

• Use SQL to query data in Snowflake.
• Update Snowflake data models, consistent with current data architecture. 
• Use LookML to add new dimensions, measures, table calculations, and explores to Looker .
• Create dashboards in Looker and Post Hog to support growth, enrollment marketing, client implementation, product initiatives, and/or company OKRs. 
• Conduct deep-dive analyses using data from Snowflake and Looker to understand user behavior patterns, identify friction points in the user journey, and uncover opportunities for product enhancement. Analyses may include, but are not limited to, descriptive analytics, correlation, regression, and between-group analyses. 
• Present the results of these analyses to a cross-functional audience, translating complex data findings into actionable recommendations.
• Build externally-facing reports that provide stakeholders with clear visibility into user engagement, and feature adoption, clinical outcomes, and recommendations for optimal product use. 
• Provide data to help justify and inform decision-making around A/B tests and experiments to validate product hypotheses and measure the impact of new features or changes. 
• Use DBT to build data models and add new data sources to Snowflake. 
• Assist with updating data dictionary and ERD. 
• Communicate proactively. During onboarding, you will meet 3-5x/week with your supervisor to provide updates on ticket status and to ask questions. Asking questions outside of these meetings is expected and welcomed. 
• Work with your supervisor and relevant stakeholders to proactively discuss requirements when questions arise. 

Required Qualifications

• 3+ years of experience in product analytics, data analysis, or a related analytical role, preferably in a product-driven technology company
• Strong SQL skills and experience working with large datasets in modern data warehouses like Snowflake, BigQuery, or Redshift
• Experience with dbt or similar data transformation tools for building modular, tested, and documented data models
• Proficiency in version control systems like Git for managing code and collaborating with data and engineering teams 
• Proficiency in analytics tools such as Python or R for statistical analysis and data manipulation
• Familiarity with BI visualization tools like Looker, Tableau, or Mode
• Basic understanding of data pipeline orchestration and workflow management tools such as Airflow or similar. Familiarity with ELT/ETL processes and data integration tools like Fivetran, Stitch, or custom-built pipelines 
• Solid understanding of statistical concepts including hypothesis testing, regression analysis, and experimental design. Experience designing and analyzing A/B tests with proper statistical rigor 
• Familiarity with healthcare concepts and terminology are highly desirable 
• Strong communication skills

Background and Life at Big Health

• Backed by leading venture capital firms.
• Big Health’s products are used by large multinational employers and major health plans to help improve sleep and mental health. Our digital therapeutics are available to more than 62 million Medicare beneficiaries.
• Surround yourself with the smartest, most enthusiastic, and most dedicated people you'll ever meet—people who listen well, learn from their mistakes, and when things go wrong, generously pull together to help each other out. Having a bigger heart and a small ego are central to our values.