1mo ago

Data Scientist, Product Analytics

Switzerland·GenèveEmployee / Full-Timemid

Data ScientistData

6 views0 saves0 applied

Apply Now

Quick Summary

Requirements Summary

someone who has measurably influenced revenue, product, or

Technical Tools

Data ScientistData

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.

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.

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.

Deep product understanding and a track record of working effectively with PMs, translating product knowledge and usage data into decisions they act on.

Strong analytical track record: someone who has measurably influenced revenue, product, or GTM decisions through analysis, not just produced reports.

Comfort with the latest AI tools, and a habit of using them to work faster and sharper: You stay current as the tooling evolves and bring new approaches to the team.

Eagerness to develop: you actively grow your skills, seek feedback, and treat new tools and methods as opportunities rather than threats.

Solid SQL. You can independently query, join, and explore data without waiting for someone to prepare it for you.

Proficiency in Python for analysis, modeling, and automation. Experience with ML and statistical libraries (e.g. scikit-learn, statsmodels) for modeling, prediction, and inference.

Statistical foundation: experimentation, significance testing, regression, segmentation, forecasting, and the judgment to know which applies.

Working knowledge of how product usage connects to revenue: funnels, cohorts, retention, account health, and the realities of joining product usage data with CRM and sales data.

Willingness to get hands-on with data modeling. You don't need to be a dbt expert, but you must be comfortable exploring messy data and partnering on (or building) the models you need rather than waiting for clean tables.

Strong communication and stakeholder skills: you can challenge weak measurement respectfully and make a recommendation, not just present options.

Proactivity and autonomy: you raise your hand early, plan your own work, and look for impact without being asked.

We're intentional about this. We believe the best teams are built in the room together. Three anchor days — Mondays, Tuesdays, and Thursdays — create the collaboration rhythm that makes a hub office worth having.

Candidates need to be genuinely based in the location the role is posted — if that's not where you are today, we're happy to support relocation for the right person.

At Sonar, we believe that our diversity is our strength. We are a global company that values and respects different backgrounds, perspectives, and cultures. We are committed to fostering a diverse and inclusive work environment where everyone feels valued and empowered to contribute their best. We are proud to be an equal opportunity employer and welcome all qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

If you need any accommodation, please reach out to us at hiring@sonarsource.com.

All offers of employment at Sonar are contingent upon the results of a comprehensive background check and reference verification conducted before the start date.

Applications that are submitted through agencies or third party recruiters will not be considered.