Data Scientist, Product Analytics

Posted 4 Hours Ago
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Geneva, CHE
Hybrid
Entry level
Artificial Intelligence • Cloud • Security • Software
Sonar is the trust & verification layer for AI and agentic coding, and the industry standard for automated code review.
The Role
Own product-usage analytics from exploration and experimentation through actionable insights. Analyze adoption, engagement, retention, expansion, churn risk, and account health by connecting product, customer, and sales data. Build usage-based signals, validate predictive metrics statistically, partner with data engineers on warehouse models, and communicate recommendations that influence product and go-to-market decisions.
Summary Generated by Built In
Who is Sonar?

Sonar is driving the future of agent-centric software development. As the leader in AI code verification and governance, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable.

Integrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code.

We believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, ServiceNow, Booking.com, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like:

  • SonarQube: The world’s leading AI code review and verification platform.
  • SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair.
  • SonarSweep & Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective.

Our team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. We move with a mindset we call CODE:

  • Committed to our customers and community.
  • Obsessed with quality.
  • Deliberate in our decisions.
  • Effective as one team.

With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you.

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 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.

In-office culture

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.


We value diversity, equity, and inclusion

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 [email protected]

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. 

Skills Required

  • Deep product understanding and experience partnering effectively with product managers
  • Demonstrated analytical impact on revenue, product, or go-to-market decisions
  • Comfort using current AI tools to improve productivity and analytical work
  • Willingness to continuously develop skills and adopt new tools and methods
  • Solid SQL skills for independently querying, joining, and exploring data
  • Python proficiency for analysis, modeling, and automation
  • Experience with machine learning and statistical libraries such as scikit-learn and statsmodels
  • Statistical knowledge of experimentation, significance testing, regression, segmentation, and forecasting
  • Understanding of product usage metrics, funnels, cohorts, retention, account health, CRM, and sales data
  • Willingness to perform hands-on data modeling and work with messy data
  • Strong communication, stakeholder management, and recommendation skills
  • Proactivity, autonomy, and ability to plan work independently

What the Team is Saying

Kim
Elizabeth
Katie
Jeff
Brian
Will
Varsha
Max
London

Sonar Compensation & Benefits Highlights

  • Leave & Time Off Breadth Time off is described as generous in the U.S., with 25 PTO days and additional days based on seniority or circumstances, alongside a hybrid rhythm with two weekly work‑from‑home days. Commuter support (public transit reimbursement and free parking) complements the time‑off offering.
  • Healthcare Strength Medical coverage includes 90% of employee premiums (60% for dependents), company‑paid life and disability insurance, telemedicine, an EAP, and HSA/FSA options, plus supplemental plans and pet insurance. This represents a broad health and protection suite.
  • Retirement Support A 401(k) with a company match up to 4% of gross salary is available in the U.S. Some locations also highlight meaningful employer pension contributions.

Sonar Insights

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The Company
HQ: Austin, TX
800 Employees
Year Founded: 2008

What We Do

Sonar provides the essential verification layer for the AI-driven development era, ensuring all code—whether human-written or AI-generated—is code you can trust. Today, AI coding tools are generating explosive volumes of code. This has created an "engineering productivity paradox" : faster code writing doesn't automatically lead to faster, safer software delivery. The new bottleneck is verification. Sonar solves this. Integrating code quality and code security into a single platform (SonarQube), Sonar is the foundation for high performance software engineering, analyzing over 750 billion lines of code daily to ensure applications are secure, reliable, and maintainable. As an independent verification platform, Sonar enables organizations to securely develop at the speed of AI. We are driven by a deep belief in our people, a commitment to excellence, and an unwavering dedication to delivery. We operate as a united group where our collective success is the sum of each individual's contributions. Our company culture is driven by the values of CODE: Committed, Obsessed, Deliberate & Effective. This mindset reflects our culture of creativity, collaboration, and pride in the work we do. Rooted in the open source community, Sonar’s solutions support over 35 programming languages, frameworks, and infrastructure technologies. Today, Sonar is used by 7M+ developers worldwide, including ServiceNow, Booking.com, Deutsche Bank, AstraZeneca, and Ford Motor Company. Sonar is headquartered in Geneva, Switzerland with additional offices in Austin, Texas; Bochum, Germany; London, Singapore, and Tokyo. The company is rapidly growing with over 800 employees! Join us in our mission to solve the trillion-dollar challenge of bad code!

Why Work With Us

We are a product-first company, with a people-first culture. Every employee has the opportunity to grow and learn. We promote from within, provide regular feedback and professional development opportunities, value the right to fail along with respect and kindness and work with team members to achieve their full potential.

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Sonar Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

At Sonar, we require employees to come into the office 3 days/week.

Typical time on-site: 3 days a week
HQAustin, TX office
Geneva Office (HQ)
Annecy Office
Bochum Office
London Office
Singapore Office
Learn more

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