Product Analyst

About the role

This role focuses on building a comprehensive analytics system for internal tools, starting from the ground up. The analyst will be responsible for designing event tracking, defining how data from both frontend and backend systems connects, and contributing to the overall data architecture. This foundational work is crucial for enabling the support team to operate more efficiently.

A key part of the work involves close collaboration with engineering teams to define analytics requirements and ensure data quality post-implementation. The analyst will also partner with data engineering to design data marts, ensuring that data is accessible and usable for analysis. Success in this role means establishing clear metrics, building dashboards, and setting up ongoing monitoring to track product performance.

Beyond system building, the analyst will analyze product usage, feature performance, and prepare analytical reports to uncover actionable insights. This includes investigating user and operational workflows to support informed product decisions. The role also involves partnering with the product manager on prioritization and shaping analytical questions, with future contributions to A/B testing setup and analysis.

The salary for this role ranges from $92,000 to $149,500 USD, paid in USD regardless of location.

Skills that matter here

• SQL: Advanced SQL skills are required for working with analytical functions, streaming data, and combining data from various sources.
• Python: Python is used for analyzing data, supporting the analytical insights and reporting.
• data analytics: This role requires experience in data analytics, specifically in designing event tracking and building analytics systems from scratch.
• data architecture: The analyst will contribute to the overall data architecture, defining how frontend and backend data should be connected.
• A/B testing: A solid understanding of mathematical statistics and A/B testing fundamentals is necessary, with future responsibilities including setting up and analyzing tests.

Who this role suits

• Someone with at least three years of experience in data or product analytics.
• A person who thrives in an environment where processes are still being established and requires a high degree of autonomy.
• An individual who pays close attention to data quality, consistently validating and double-checking results.
• A candidate who can clearly visualize data and build intuitive, actionable reports.

From the employer

• Build product analytics from scratch: design event tracking, define how frontend and backend data should be connected, and contribute to the overall data architecture.
• Work closely with engineers to define analytics requirements and validate data quality after implementation.
• Partner with the data engineering team to design data marts and ensure data is accessible and usable for analysis.
• Define key product metrics, build dashboards, and set up ongoing monitoring.
• Analyze product usage and feature performance, prepare analytical reports, and uncover actionable insights.
• Investigate current user and operational workflows to help the team make informed product decisions.
• Partner with the product manager on prioritization and help shape analytical questions and hypotheses.
• In the future, contribute to the setup and analysis of A/B tests.

• 3+ years of experience in data analytics or product analytics.
• Experience designing event tracking and building analytics systems from scratch.
• Strong understanding of how frontend and backend data connect, and how to design a reliable analytical data model.
• Advanced SQL skills, including analytical functions, working with streaming data, and combining data from multiple sources.
• Experience analyzing data with Python.
• Solid understanding of mathematical statistics and the fundamentals of A/B testing.
• Ability to visualize data clearly and build intuitive, actionable reporting.
• High level of autonomy and proactivity, with the ability to work effectively in an environment where many processes are still being established.
• Strong attention to data quality and a habit of validating and double-checking results.

• Work from anywhere in the world: no location restrictions, salary paid in USD, travel-loving culture.
• No bureaucracy: efficient processes, horizontal and open communication, quick idea discussion and decision-making.
• Benefits compensation: private medical insurance, psychotherapy or language courses, sports activities, and sick leave.