5+ years of relevant experience in analytics, working with business KPIs and metrics, of which 2+ working closely with product managers and user research teams.
Fluency in SQL (essential)
Data visualization tools such as Tableau, PowerBI or similar (essential)
Familiar with event-tracking tools such as Google Analytics, Amplitude or similar (essential)
Familiar with Python and its ecosystem of Data Science libraries
Experience working with data warehouses (Redshift, Bigquery etc.)
Great communication skills and stakeholder management.
Fluent in manipulating, transforming, and reshaping data, preferably from multiple data sources.
Doing root-cause analysis, applying statistical concepts like regressions, and proving correlations and causation.
Contributing to data warehouses, creating aggregated data sets, general understanding of data pipelines and flows.
Experience running A/B Tests and interpreting the results.
Responsibilities:
Create and maintain dashboards, analyses, and forecasts related to our team’s main metrics.
Work with higher management, business stakeholders, and researchers to create and validate hypotheses from both a qualitative and quantitative perspective.
Manipulate and transform large data sets to bring new insights and perform root-cause analysis.
Effectively communicate and present findings, insights, and recommendations to various stakeholders and a wider audience.
Help shape our product strategy with data-driven insights, defining our main metrics and customer journeys.
Work closely with Data Engineering to maintain and improve data sources used in some of our main dashboards.
Ensure the visibility of customer interactions by defining specs for software instrumentation and provide access to enable your stakeholders to take decisions based on product usage and interactions.
Analyze funnels and Conversion rates, and validate hypotheses by taking the lead on experiments and A/B Tests.