About the Role
Role details below.
Responsibilities
- Help product areas to strategically build the product by bringing ideas for new growth opportunities based on expertise, estimating potential impact, and guiding strategy through metric frameworks and insights
- Work with higher management, business stakeholders, and researchers to create and validate hypotheses from both qualitative and quantitative perspectives
- Create and maintain dashboards, analysis, and forecasts related to the team’s main metrics
- Manipulate and transform large datasets to bring new insights and perform root-cause analysis
- Collaborate with the Product team to test new features and validate hypotheses through experimentation and A/B testing
- Perform segmentation analysis to understand who customers are and what drives their engagement with products
- Work closely with Data Engineering to maintain and improve data sources used in main dashboards
Requirements
- 5+ years of relevant experience in analytics, working with business KPIs and metrics
- 2+ years of experience working closely with product managers and user research teams
- Proficiency in SQL (essential)
- Experience with DBT
- Data visualization tools such as Tableau, PowerBI or similar (essential)
- Event-tracking tools such as Google Analytics, Amplitude or similar (essential)
- Python and its ecosystem of Data Science libraries
- Great communication skills and stakeholder management
- Ability to translate complex analyses into clear insights that executives and stakeholders act on
- Fluent in manipulating, transforming, and reshaping data, preferably from multiple data sources
- Experience doing root-cause analysis, applying statistical concepts like regressions, and proving correlations and causation
- Experience contributing to data warehouses, creating aggregated data sets, and general understanding of data pipelines and flows
- Experience designing, implementing, and measuring A/B tests and interpreting the results
- Experience enabling others by training stakeholders on tools and helping teams become more data-literate and autonomous
Nice to Have
- Familiarity with complex Product organizations in the SaaS market
- Enjoyment of using cutting-edge tools, frameworks, and incorporating AI to automate and improve work
