Product Analyst

About the role

This role focuses on building a complete analytics framework for the Backoffice Support team, which develops internal tools to enhance operational efficiency. The Product Analyst will be responsible for everything from initial event design and data architecture to defining key metrics, setting up monitoring, and conducting product research. Success in this position means providing clear, actionable data insights that directly influence product decisions and improve internal workflows.

The analyst will work closely with engineering teams to define analytics requirements and ensure data quality, and will partner with data engineering to create accessible data marts. A core part of the job involves analyzing product usage, reporting on feature performance, and investigating user workflows to inform product development. This position requires a high degree of autonomy, as many processes are still being established.

Key responsibilities also include collaborating with the product manager on prioritization and formulating analytical questions and hypotheses. While not an immediate focus, the role will eventually involve contributing to the setup and analysis of A/B tests. This position is suited for someone who can drive the analytical agenda, ensuring that data is not only collected but also effectively utilized to guide product strategy.

The salary for this role is listed between $92,000 and $149,500 USD.

Skills that matter here

• SQL: Advanced SQL skills are essential for managing streaming data, combining diverse data sources, and performing analytical functions.
• Python: Python will be used for data analysis, complementing SQL in uncovering insights from product data.
• data analytics: This role requires comprehensive data analytics experience, from designing systems to interpreting results and influencing product strategy.
• data architecture: The analyst will contribute to the overall data architecture, defining how frontend and backend data connect for reliable analysis.
• A/B testing: A solid understanding of A/B testing fundamentals is required, with future responsibilities including test setup and analysis.

Who this role suits

• You have a proactive and autonomous work style, comfortable establishing processes rather than following existing ones.
• You possess a strong attention to detail, consistently validating and double-checking data results to ensure accuracy.
• You are adept at translating complex data into clear, actionable reports and visualizations.
• You thrive in environments where you can influence product decisions through data-driven insights.

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.