Senior Growth Analyst - Calendars

Accountabilities:: Transform and analyze large datasets using BigQuery, Amplitude, and related tools to identify product and growth opportunities, trends, anomalies, and actionable insights across the user journey. Build and maintain self-serve reports and dashboards that help stakeholders answer key business questions and establish reliable sources of truth for growth metrics. Define, document, and QA event structures for new features, campaigns, and experiments while developing robust measurement systems for monetization, pricing, and migration initiatives. Analyze user funnels across advertising, app stores, onboarding, in-product engagement, purchases, cancellations, and renewals to identify drop-offs and opportunities for improvement. Design, sequence, and monitor A/B experiments and feature launches, validating results with appropriate statistical rigor and tracking long-term impact. Proactively identify insights, hypotheses, and growth opportunities and collaborate with product and marketing teams to shape quarterly priorities and roadmap decisions. Develop forecasting and scenario models covering installs, conversion, retention, revenue, and other key growth metrics. Maintain data integrity across analytics tools and pipelines through established QA processes and collaborate with measurement vendors to improve attribution and acquisition reporting. Requirements: 4+ years of experience in growth, product, or marketing analytics within a B2C or SaaS environment. Experience supporting user acquisition, pricing, monetization, migration, or other growth initiatives for subscription-based products. Strong SQL skills and experience with BigQuery or comparable cloud data warehouses such as Snowflake or Redshift. Proficiency with reporting and visualization platforms such as Tableau or Looker and product analytics tools such as Amplitude, Mixpanel, Heap, Hotjar, or PostHog. Experience with marketing attribution platforms such as AppsFlyer, Adjust, or Kochava. Familiarity with Python or R for data analysis and automation; experience with machine learning or time-series inference is a strong advantage. Strong understanding of product analytics, including funnels, cohorts, retention, event tracking, segmentation, churn, and lifetime value. Solid knowledge of marketing analytics, attribution, marketing mix modeling, incrementality testing, statistics, and experimentation. Advanced analytics experience involving causal inference, quasi-experiments, econometrics, linear programming, or similar methodologies is highly advantageous. Proven ability to build self-serve analytics solutions and act as a strategic thought partner to product and marketing teams rather than simply responding to reporting requests. Strong business acumen with the ability to translate complex analysis into clear recommendations and measurable business outcomes. Proactive, curious, collaborative, and coachable mindset, with the ability to work effectively across product, marketing, and engineering teams. Benefits: Customer-centric culture focused on creating meaningful experiences for millions of users. Opportunity to directly influence product, marketing, monetization, and growth strategies through data-driven insights. Strong focus on professional growth, ownership, continuous learning, and feedback. Collaborative environment with experienced and supportive cross-functional teams. Opportunity to work on products with tangible, measurable impact. Culture that encourages curiosity, creativity, experimentation, and innovation. Exposure to advanced analytics, experimentation, product growth, subscription economics, and large-scale customer data. Opportunity to contribute to strategic decisions and help shape the future direction of a widely used productivity product.