Data Scientist, Marketing Analytics in London

Data Scientist, Marketing Analytics in London

London Full-Time 60000 - 80000 £ / year (est.) No working from home possible
SonarSource

At a Glance

  • Tasks: Transform marketing data into actionable insights and drive strategic decisions.
  • Company: Join Sonar, a leader in AI code verification and governance.
  • Benefits: Competitive salary, relocation support, and a collaborative office culture.
  • Other info: Diverse and inclusive workplace with excellent career growth opportunities.
  • Why this job: Make a real impact in the fast-paced world of AI-driven marketing analytics.
  • Qualifications: Strong analytical skills, proficiency in SQL and Python, and a proactive mindset.

The predicted salary is between 60000 - 80000 £ per year.

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: This role is the data team's dedicated analytical partner for Marketing. Your core job is to turn marketing data into decisions: diagnose what is working and what is not, explain why, and recommend where to spend the next dollar. You will own marketing attribution, ROI, and conversion analysis end to end, and you will be proactive about it, surfacing findings and opportunities before anyone asks.

You will explore data, form hypotheses, and partner with our Data and Analytics Engineers to shape the models and pipelines you need. You will help define those models, but your primary measure of success is the quality and impact of your analysis. This role sits in the Data & Insights team and partners closely with Marketing, IT/Marketing Ops, Data Engineers, Analytics Engineers, and data scientists covering other domains.

What you will do:

  • Drive marketing decisions with analysis. Own attribution, ROI, conversion, and funnel analysis. Diagnose drops and anomalies, quantify what drives them, and translate findings into clear recommendations for marketing leaders.
  • Optimize marketing spend. Connect spend to outcomes across channels and campaigns, and advise on where to invest, cut, or test next.
  • Be proactive. Explore and correlate data to surface insights nobody asked for. Anticipate the next question. Bring opportunities to the marketing team rather than waiting for requests.
  • Run experiments. Design and read out A/B tests and other experiments, applying sound statistical methods and being honest about significance and causality.
  • Partner on the data foundation. Work hand in hand with Data Engineers and Analytics Engineers to get marketing data into the warehouse and modeled. Define requirements, explore raw data, and contribute to data models that connect marketing data with sales and product data.
  • Tell the story. Communicate insights so non-technical stakeholders can act, and document context, caveats, and decisions so the work survives handoffs.

Experience and qualifications:

  • Strong analytical track record: someone who has measurably influenced business or marketing decisions through analysis, not just produced reports.
  • Comfort with the latest AI tools, and a habit of using them to work faster and sharper: exploring data, writing and debugging code, drafting analysis, and accelerating insight. 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.
  • Statistical foundation: experimentation, significance testing, regression, segmentation, forecasting, and the judgment to know which applies.
  • Working knowledge of marketing and GTM data: channels, campaigns, attribution models, funnel and conversion metrics, and the realities of joining marketing data to CRM/sales and product usage 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.

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

Data Scientist, Marketing Analytics in London employer: SonarSource

At Sonar, we pride ourselves on being an exceptional employer, offering a dynamic work culture that thrives on collaboration and innovation. Our commitment to employee growth is evident through our supportive environment, where diverse perspectives are valued, and opportunities for professional development abound. Located in vibrant hubs like London, we foster a sense of community while driving the forefront of AI software development, making it an exciting place for passionate individuals to make a meaningful impact.

SonarSource

Contact Details:

SonarSource Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist, Marketing Analytics in London

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like SonarSource.

Apply Directly through Our Website

When you find a suitable opening like Data Scientist, Marketing Analytics at SonarSource, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Scientist, Marketing Analytics in London

Analytical Skills
Marketing Attribution
ROI Analysis
Conversion Analysis
Data Exploration
SQL
Python

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at SonarSource, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at SonarSource. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at SonarSource

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SonarSource!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.