About the role
The Product Analyst will own metrics, experimentation, and data quality for SMP and SMD products. They will build dashboards, run A/B tests, and utilize AI agents to automate analytics workflows and drive decision-making.
What they look for
Requirements
Candidates must have strong SQL and Python skills, along with experience in A/B testing and statistical modeling. Proficiency in using AI coding and analytics tools like Claude Code, Cursor, or ChatGPT in a professional capacity is required.
Full description
We're looking for a Product Analyst to own metrics, experimentation, and data quality for SMP and SMD. You'll be at the center of how the team makes decisions — building the dashboards people check daily, running the A/B tests that validate product hypotheses, and increasingly, using AI agents to move faster without sacrificing rigor. This is a hands-on analytics role for someone who already treats tools like Claude Code, Cursor, or ChatGPT as part of their daily workflow, not a novelty
We are actively integrating AI and automation into all areas of the business and expect candidates with a mindset focused on improving efficiency and delivering a better experience.
Key responsibilities
- Own and track key metrics for SMP and SMD products: dashboards and regular reporting
- Launch and analyze experiments and A/B tests: validate hypotheses, run the test, deliver conclusions
- Use AI agents (Claude Code or similar) for day-to-day analytics work and verify their output before it goes to stakeholders
- Turn recurring analyses into reusable AI skills and automated pipelines
- Ensure data accuracy, consistency, and completeness across sources
- Identify trends, anomalies, and insights to guide decision-making
- Document metric definitions, data sources, and known data issues so both people and AI tools can rely on them
Requirements
- Daily use of AI coding/analytics tools (Claude Code, Cursor, ChatGPT or similar) in real work, not as an experiment
- Strong SQL: enough to review and fix generated queries quickly
- Python for data cleaning and analysis
- Strong understanding of A/B testing methodologies
- Solid math and statistics for modeling and hypothesis testing
- Experience with data visualization tools (e.g., Redash, Metabase, Tableau)
- Ability to write clear task descriptions and documentation
- Collaboration and problem-solving skills
- Upper-intermediate English level
Benefits
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