Senior Data Analyst

📋 Description

• • Partner with Product Owners and Data Teams across marketing, billing, and product domains to align analytics strategy with business objectives.
• • Create, maintain, and improve dashboards and reports including Product Reports to enable data-driven decision-making across the organization.
• • Perform user behavior analysis and aha moment analysis to uncover key engagement patterns and improve product experience.
• • Analyze large datasets to identify trends, patterns, and actionable insights that maximize KPIs and drive product growth.
• • Design and conduct A/B tests and homogeneity tests to validate hypotheses and measure the impact of product changes.
• • Monitor key metrics across all business domains to ensure data accuracy, consistency, and real-time visibility.
• • Design and build robust, scalable data models using SQL to support reporting and analytical needs.
• • Translate complex data findings into clear, strategic recommendations for product, marketing, and leadership teams.
• • Give and receive actionable feedback from peers and the Leadership Team to continuously improve analytical processes and outcomes.
• • Own end-to-end data pipelines from extraction to visualization, ensuring data integrity and reliability across all analytical outputs.
• • Work with product analytics tools including Mixpanel, GA4, Amplitude, or similar to track user journeys and behavioral metrics.
• • Collaborate in a fast-paced, high-pressure environment where rapid iteration and data accuracy are critical to product success.
• • Adapt quickly to evolving data needs, new tools, and shifting priorities in a rapidly scaling consumer product.
• • Ensure all analyses are aligned with company goals and contribute directly to improving user acquisition, retention, and conversion.
• • Communicate findings effectively through verbal presentations and clear written summaries to stakeholders at all levels.
• • Work within the CET timezone (+/- 4 hours) to ensure seamless collaboration with cross-functional teams.
• • Maintain a strong focus on data quality, validation, and documentation to uphold the integrity of all analytical outputs.
• • Contribute to the development of benchmarks and standards for performance measurement across product and marketing channels.
• • Support subscription-based business analytics by analyzing cohort retention, churn, LTV, and MRR trends.
• • Engage in continuous learning to stay current with evolving data tools, methodologies, and industry best practices.
• • Participate in an iterative interview process including recruiter screening, technical assessment, and final leadership review.