Data Scientist, Product Analytics

Arovy; Genf; On-site; CHF 120,000 - 180,000; Full time

Job summary

Sonar is seeking a data‑driven product analytics professional to decode customer behaviors and transform product engagement into actionable intelligence. You will own the product usage analytics lifecycle, perform hands‑on data exploration, hypothesis testing, and collaborate with Data and Analytics Engineers to model the foundations you require.

This role partners with the Product, Engineering and Sales teams to link usage to outcomes, define usage signals, run experiments, and tell clear

Qualifications

• Deep product understanding and a track record of working effectively with cross‑functional teams.

Responsibilities

• Understand product usage with PMs to analyze adoption, engagement, retention.
• Connect usage to outcomes by linking product usage data with customer and sales data.
• Define usage-based signals and metrics that translate behavior into insights.
• Be proactive in exploring product, sales, and customer data to surface findings.
• Run experiments and validate which usage signals predict outcomes using sound methods.
• Partner with Data and Analytics Engineers to get product and sales data into the warehouse and modeled well.
• Tell the story by communicating insights clearly and documenting context and decisions.

Job description

Who is Sonar?

Sonar enables organizations to ship agentic code with confidence. Code creation is abundant, but confidence is scarce. Our core platform, SonarQube, verifies over 750 billion lines of code every day, delivering agentic verification and governance for all code. Trusted by more than 7 million developers and 75% of the Fortune 100, including teams at Nvidia, ServiceNow, Booking.com, Goldman Sachs, AstraZeneca, and Ford Motor Company, Sonar enables organizations to reduce outages, improve security, and lower the cost and risk of agentic software development.
Founded in Geneva and now headquartered in Austin, Texas, Sonar has a global team working across offices and hubs, including Silicon Valley, London, Bochum, Barcelona, Singapore, Tokyo, and the Washington, D.C. area. At Sonar, we’re enabling enterprises to build agentic software factories that can move quickly while maintaining the control, consistency and evidence required to ship with confidence.

Position description

Operating within the Data & Insights team, your mission is to decode customer behaviors and transform product engagement into high-impact, actionable intelligence. By bridging the gap between product adoption and commercial data, you will construct a holistic view of user health and the tangible value we provide.

You will take full ownership of the product-usage analytics lifecycle. This involves hands‑on data exploration, hypothesis testing, and deep collaboration with Data and Analytics Engineers to architect the foundational models you require. Success is defined by analytical rigor and your ability to steer strategic product and Go‑to‑Market (GTM) decisions.

Embedded in our central Data & Insights department, this role serves as a strategic partner to our Product organisation, driving cross‑functional synergy with other departments, engineering, and data science teams to maximize overall success.

Success depends on genuinely understanding the product you're analyzing, not just the data behind it.

What you will do

• Understand product usage. Work closely with product managers (PMs), building a deep understanding of the product itself, to analyze how customers adopt and use it, and identify patterns in engagement, feature usage, and retention.to Analyze how customers adopt and use the product, and identify patterns in engagement, feature usage, and retention.

• Connect usage to outcomes. Link product usage data to customer and sales data to reveal how usage relates to expansion, churn risk, and account health.

• Define usage‑based signals. Build the logic behind usage scoring, health indicators, and other metrics that translate behavior into insights that drive activation, retention, and expansion.

• Be proactive. Explore product, sales, and customer data to surface findings nobody asked for. Anticipate the next question.

• Run experiments and validate. Test which usage signals actually predict outcomes, applying sound statistical methods and being honest about significance and causality.

• Partner on the data foundation. Work with Data and Analytics Engineers to get product and sales data into the warehouse and modeled well. Define requirements and contribute to data models that connect product usage with customer and sales data.

• Tell the story. Communicate insights clearly to stakeholders across the business, and document context, caveats, and decisions so the work survives handoffs.

Experience and qualifications

• Deep product understanding and a track record of working effectively with