At JetBrains, we're building an AI-native platform for software development that connects developer workflows, team-level collaboration and organizational control into a single coherent system. This platform will serve as the execution and governance layer for AI-driven development, deeply integrated with developer tools but designed to work across teams, products and environments. This is a long-term strategic investment for JetBrains and a key pillar of our vision for the future of software development.

The analytics team plays a key role in supporting the platform's success, leveraging quantitative methods to drive both product and business excellence. Data analysts provide actionable insights into platform usage and expenses, user behavior, and adoption, ensuring optimal performance of AI-driven features while helping to shape the product roadmap. They monitor and optimize platform metrics and provide data to guide decisions about resource allocation, feature prioritization and long-term scalability.

In this role, you will: 

• Create and maintain dashboards to track product usage and key business metrics.
• Derive insights from billing data to back up product development decisions.
• Analyze current and projected costs for AI platforms.

We value data analysts who: 

• Communicate effectively and clarify ambiguous requests.
• Ensure each analytics request has a well-defined business value.
• Collaborate comfortably with diverse stakeholders.
• Plan their work and make decisions independently, consulting others as needed.
• Proactively delve into topics to account for all relevant details.

We'll be happy to have you on our team if you have: 

• Expertise in statistics and data analysis.
• Extensive experience with SQL and Python.
• At least two years of experience with Tableau, Power BI, or other BI tools.
• Data visualization and interpretation skills.

We'd be especially thrilled if you: 

• Have experience with LLM-related analytics.
• Can distill complex analyses into clear, straightforward explanations.

In the AI Analytics team, we use: 

• SQL for data querying.
• Python for data processing and visualizations.
• TeamCity for data pipelines.
• Datalore and Excel for composing analytical reports.

#LI-DNI