Senior Data Analyst

Role overview Use product and business data to guide decisions across a software product’s lifecycle. This senior individual contributor role combines analytical modeling, experimentation, dashboard development, and strategic partnership with product managers and other stakeholders. You’ll turn complex findings into recommendations that shape product priorities, adoption, retention, and growth.

Responsibilities - Build reliable data processes and reusable models that support consistent analytical reporting and product metrics. - Create and maintain clear dashboards and reporting tools for product teams, internal stakeholders, and executives. - Define and monitor measures of acquisition, adoption, retention, and monetization with relevant stakeholders. - Analyze user behavior, feature usage, and experiment results to assess product changes and their effects on engagement, retention, and revenue. - Develop churn and activation analyses or models that help improve customer lifetime value. - Present concise, actionable findings to technical and non-technical audiences, and help shape an analytics roadmap aligned with business goals. - Work with product, engineering, and cross-functional teams to inform prioritization; mentor colleagues on analysis and communication practices.

Requirements - At least five years of data analysis experience, ideally supporting product teams in a SaaS or technology setting. - Strong SQL skills, including writing and optimizing complex queries against large datasets. - Experience with data modeling, such as dimensional modeling or dbt, and building documented, reusable sources of truth for metrics. - Advanced ability with dashboard and visualization platforms; experience with tools such as Metabase, Pigment, or QuickSight is relevant. - Practical experience with product adoption analysis, A/B testing, statistical analysis, and defining product metrics. - Ability to translate analysis into recommendations, communicate with stakeholders at different levels, and manage competing priorities. - Fluent English and comfort working independently as well as collaboratively.

Nice to have - Experience using AI-assisted coding or analytics tools to speed up query, model, or insight development while checking results carefully. - Additional language skills.