Data Analyst (JetBrains AI)

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

The JetBrains AI department is working on a platform that provides AI capabilities to all JetBrains products. Our platform is based on in-house developed models for writing and coding assistance, as well as integration with LLMs such as those from OpenAI and Google.

The JetBrains AI Analytics team uses quantitative methods to help develop AI-based products. We provide analytics to support product and marketing strategies, optimize AI expenses, and ensure our infrastructure can sustainably handle the necessary LLM workload. We are looking for a Data Analyst to help analyze platform usage and billing data from AI-based JetBrains products.

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.