Sonar Source

4 weeks ago

Data Scientist, Marketing Analytics

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Data Scientist focused on turning marketing data into decisions through attribution, ROI, and conversion analysis. You’ll optimize spend across channels, run experiments with solid statistics, and collaborate with Data Engineers to model marketing data for actionable insights.

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own marketing attribution, ROI, and conversion analysis end to end, turning data into actionable insights.
•Diagnose drops and anomalies, quantify drivers, and translate findings into clear recommendations for marketing leaders.
•Optimize marketing spend by connecting spend to outcomes across channels and campaigns, advising on where to invest, cut, or test next.
•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 with Data Engineers and Analytics Engineers to get marketing data into the warehouse and modeled; define requirements and contribute to data models that connect marketing data with sales and product data.

Key Requirements

•Strong analytical track record: someone who has measurably influenced business or marketing decisions through analysis, not just produced reports.
•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.

Experience:Marketing analyticsData analyticsAI tools

Education:Bachelor's

Skills:CommunicationStakeholder managementProblem-solvingPresentationStorytelling

Languages:English

Tech Stack:PythonSQLData warehouseA/B testingStatistical analysis

Company Brief

Sonar Source

Builds static code analysis and continuous inspection tools (SonarQube, SonarCloud, SonarLint) that identify bugs, vulnerabilities, and code smells across multiple languages to help teams improve code quality and maintainability.

Industry: Developer Tools

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Headquarters: Geneva, Switzerland

Founded: 2008

Website LinkedIn

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Sonar Source

4 weeks ago

Data Scientist, Marketing Analytics

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own marketing attribution, ROI, and conversion analysis end to end, turning data into actionable insights.
•Diagnose drops and anomalies, quantify drivers, and translate findings into clear recommendations for marketing leaders.
•Optimize marketing spend by connecting spend to outcomes across channels and campaigns, advising on where to invest, cut, or test next.
•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 with Data Engineers and Analytics Engineers to get marketing data into the warehouse and modeled; define requirements and contribute to data models that connect marketing data with sales and product data.

Key Requirements

•Strong analytical track record: someone who has measurably influenced business or marketing decisions through analysis, not just produced reports.
•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.

Experience:Marketing analyticsData analyticsAI tools

Education:Bachelor's

Skills:CommunicationStakeholder managementProblem-solvingPresentationStorytelling

Languages:English

Tech Stack:PythonSQLData warehouseA/B testingStatistical analysis

Company Brief

Sonar Source

Industry: Developer Tools

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Headquarters: Geneva, Switzerland

Founded: 2008

Website LinkedIn