Senior Data Analyst, Lifecycle Marketing

About this role

Thrive Market is seeking a Senior Data Analyst focused on Lifecycle Marketing to turn data into strategic insights that guide the Lifecycle Marketing team. The role involves translating complex data into clear recommendations, collaborating with cross-functional partners, and supporting campaigns and retention initiatives. You will work as an analytics partner to Thrive Market leaders, helping connect data to business outcomes and improve decision-making. The position reports to the Senior Manager, Data Analytics & Engineering and sits within Thrive Market’s data-driven organisation. The role includes supporting retention and engagement analytics, modelling, and informing CRM and lifecycle strategies.

What you would do

• Lead end-to-end analytics projects that influence business and product strategy.
• Collaborate with stakeholders to align priorities and translate questions into analytical frameworks.
• Deliver data-driven insights to inform decisions across the organisation.
• Design and maintain dashboards, models and datasets for self-serve analytics.
• Identify and help resolve data quality issues across source systems.
• Support lifecycle and engagement analytics to improve retention and lifetime value.
• Work with Finance to measure and forecast financial impact of decisions.
• Respond to ad hoc analytical requests with accuracy and context.
• Propose enhancements to analytics processes and tooling.
• Partner with the Retention Marketing team to evaluate customer journeys and measure email, SMS and app engagement campaigns.

What they are asking for

• 7+ years of data analytics experience with demonstrated business impact.
• MBA with analytics, strategy or related quantitative focus.
• Ability to translate business questions into analytical frameworks and provide actionable insights.
• Proficiency in SQL and data visualization tools (Domo, Looker, Tableau) with self-serve governance.
• Advanced SQL skills and experience with Snowflake or BigQuery.
• Experience using DBT and Python for data manipulation.
• Strong foundation in statistics and multivariate regression.
• Experience building and interpreting member segmentation models for lifecycle campaigns.
• Proven track record with A/B and multivariate testing across channels (email, SMS, push, onsite).
• Ability to communicate insights to non-technical audiences and influence decisions.

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