Own web and product analytics across markets, improving online conversion through reliable tracking, booking-funnel analysis, A/B testing, and clear insights for Product and Marketing teams.
Senior Data Analyst
๐ Description
- Establish reliable data processes and models for high-quality analytical reporting.
- Build dashboards and reporting tools that give product managers and teams actionable insights.
- Define and monitor product metrics across acquisition, retention, monetization, and adoption.
- Analyze user behavior, feature usage, and A/B tests to measure product impact.
- Present clear data narratives and recommendations to technical and non-technical stakeholders.
- Develop churn models, activation metrics, and an analytics roadmap aligned with business objectives.
๐ ๏ธ Requirements
- 5+ years of experience in data analysis, ideally with product teams in a SaaS or technology environment.
- Strong SQL skills, including optimizing complex queries on large datasets.
- Experience with data visualization tools such as Metabase, Pigment, or QuickSight.
- Experience with data modeling, such as dimensional modeling or dbt.
- Hands-on experience with adoption analysis, A/B testing, and statistical analysis.
- Ability to translate complex insights into actionable recommendations and communicate effectively with stakeholders.
- Experience using AI tools to accelerate query and model development while checking accuracy.
- Fluency in English.
Full job description
About the Role:
We're looking for an experienced and strategic Senior Data Analyst to join Uberall's product team. In this role, youโll be at the heart of data-informed decision-making, working closely with product managers and stakeholders to deliver actionable insights that drive our product strategy. Your skills in distilling complex data into meaningful narratives, alongside your experience in creating intuitive dashboards, will be instrumental in supporting our growth and product innovation.
If youโre passionate about using data to tell compelling stories, enjoy structuring insights that influence product decisions, and thrive in a collaborative environment, this could be the perfect role for you. Join us in creating exceptional experiences for our clients and helping shape the future of our products. Apply today to make a tangible impact with your data expertise!
Your Responsibilities:
Establish and maintain robust processes and data models to ensure high data quality and reliability for analytical reporting.
Build and maintain impactful dashboards and reporting tools, integrating feedback from multiple sources to support product managers, other internal teams, and executives with actionable and user-friendly data visuals.
Define and monitor key product performance metrics with stakeholders, focusing on areas such as acquisition, retention, monetization, and adoption to drive product and business insights.
Collaborate with product managers, engineers, and cross-functional teams to prioritize features and drive a data-informed product roadmap.
Create clear, concise stories from data analyses, presenting findings to technical and non-technical audiences to inform product decisions and strategy.
Conduct in-depth analyses of user behavior, feature usage, and A/B test results to evaluate product changes and measure their impact on user engagement, retention, and revenue.
Develop predictive churn models and analyze product usage trends to create activation metrics that increase customer lifetime value (LTV).
Develop a strategic data analytics roadmap, aligning with key business objectives and collaborating with cross-functional leaders.
Mentor and support team members, promoting best practices in data analysis and effective communication across the organization.
Stay current on industry trends, competitor insights, and data science advancements to continuously improve analytics processes and product strategy.
Your Profile:
5+ years of experience in data analysis, ideally with experience in or close collaboration with product teams in a SaaS or technology environment.
Advanced skills in data visualization tools like Metabase, Pigment, QuickSight, or similar platforms.
Strong command of SQL, with the ability to create and optimize complex queries on large datasets.
Solid experience in data modelling (e.g. dimensional modelling, dbt or similar), designing clean, documented and reusable models that act as the single source of truth for product metrics.
Hands-on experience using AI tools (e.g. coding assistants, LLM-powered analytics) to accelerate query and model development, automate repetitive work and speed up insight generation, while keeping a critical eye on accuracy.
Proven ability to translate complex data insights into clear, actionable recommendations for cross-functional teams.
Hands-on experience with adoption analysis, A/B testing frameworks and statistical analysis, with a solid foundation in designing and analyzing experiments.
Proven experience in establishing and tracking core product metrics and driving insights that influence product development and growth initiatives.
Exceptional communication and presentation skills, adept at engaging and aligning stakeholders at all levels.
Highly organized, with strong prioritization skills to manage multiple projects and deadlines.
Comfortable working both independently and collaboratively in a dynamic, fast-paced environment.
Fluency in English is required; additional language skills are a plus.
Similar jobs
Search more Data Analyst jobsOwn marketplace economics and monetization, using analytics, experiments, and cross-functional partnerships to balance supply, demand, pricing, and user experience and drive sustainable growth.
Own marketplace economics and monetization by analyzing supply, demand, pricing, and performance, then using dashboards and experiments to improve engagement, profitability, and sustainable growth.
Drive product and business decisions through deep-dive analysis, experimentation, and actionable recommendations, while building AI-powered workflows that make analytics more efficient and accessible.
Investigate suspected fraud, analyze mobile measurement and partner data with SQL, and identify emerging abuse patterns to improve safeguards and protect legitimate users across mobile apps.
