{"active":true,"apply_url":"https://jobs.lever.co/sonarsource/c9783c31-cfa1-4d95-b31a-278cd0d14162/apply","company":{"claimed":false,"name":"Sonar","slug":"sonarsource","website":"https://www.sonarsource.com"},"countries":["CH"],"employment_type":"full-time","first_seen_at":"2026-10-28T13:00:09Z","getwork_url":"https://getwork.dev/jobs/lv-sonarsource-c9783c31-cfa1-4d95-b31a-278cd0d14162/","id":"lv-sonarsource-c9783c31-cfa1-4d95-b31a-278cd0d14162","injection_flag":false,"last_seen_at":"2026-10-28T18:45:09Z","location":"Geneva","published_at":"2026-09-07T16:07:44Z","regions":["europe"],"remote":"onsite","role_family":"data","salary":null,"seniority":"unspecified","stack":["go","python"],"stack_mentioned":[],"title":"Data Scientist, Product Analytics","untrusted_description":"Who is Sonar?\nSonar 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.\n\nFounded 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.\n\nPosition description\nOperating 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.\n\nYou 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.\n\nEmbedded 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.\n\nSuccess depends on genuinely understanding the product you're analyzing, not just the data behind it.\n\nWhat you will do\n-\nUnderstand 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.\n\n-\nConnect usage to outcomes. Link product usage data to customer and sales data to reveal how usage relates to expansion, churn risk, and account health.\n\n-\nDefine 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.\n\n-\nBe proactive. Explore product, sales, and customer data to surface findings nobody asked for. Anticipate the next question.\n\n-\nRun experiments and validate. Test which usage signals actually predict outcomes, applying sound statistical methods and being honest about significance and causality.\n\n-\nPartner 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.\n\n-\nTell the story. Communicate insights clearly to stakeholders across the business, and document context, caveats, and decisions so the work survives handoffs.\n\nExperience and qualifications\n-\nDeep product understanding and a track record of working effectively with PMs, translating product knowledge and usage data into decisions they act on.\n\n-\nStrong analytical track record: someone who has measurably influenced revenue, product, or GTM decisions through analysis, not just produced reports.\n\n-\nComfort 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.\n\n-\nEagerness to develop: you actively grow your skills, seek feedback, and treat new tools and methods as opportunities rather than threats.\n\n-\nSolid SQL. You can independently query, join, and explore data without waiting for someone to prepare it for you.\n\n-\nProficiency in Python for analysis, modeling, and automation. Experience with ML and statistical libraries (e.g. scikit-learn, statsmodels) for modeling, prediction, and inference.\n\n-\nStatistical foundation: experimentation, significance testing, regression, segmentation, forecasting, and the judgment to know which applies.\n\n-\nWorking 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.\n\n-\nWillingness 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.\n\n-\nStrong communication and stakeholder skills: you can challenge weak measurement respectfully and make a recommendation, not just present options.\n\n-\nProactivity and autonomy: you raise your hand early, plan your own work, and look for impact without being asked.\n\nIn-office culture\nWe'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.\nCandidates 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.\n\nWe value diversity, equity, and inclusion\nAt 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.\nIf you need any accommodation, please reach out to us at hiring@sonarsource.com.\nAll offers of employment at Sonar are contingent upon the results of a comprehensive background check and reference verification conducted before the start date.\nApplications that are submitted through agencies or third party recruiters will not be considered.","url":"https://jobs.lever.co/sonarsource/c9783c31-cfa1-4d95-b31a-278cd0d14162"}