Data Scientist (Marketing Analytics)

Join our Data & Insights team as a Data Scientist focused on Marketing Analytics. In this role, you will analyze marketing data to drive decisions, optimize marketing spend, run experiments, and partner on data foundation. You will communicate insights to non-technical stakeholders and document context, caveats, and decisions. Enjoy a comprehensive benefits package, including a 401K plan, healthcare coverage, and generous time off.

• Analyser les données marketing pour identifier les tendances, les opportunités et les domaines d'amélioration, et formuler des recommandations basées sur ces analyses.
• Gérer l'attribution marketing, le retour sur investissement (ROI) et l'analyse de conversion de manière proactive, en identifiant les résultats et les opportunités avant qu'on ne vous le demande.
• Collaborer avec les ingénieurs en données et les ingénieurs en analytique pour façonner les modèles et les pipelines nécessaires à l'analyse des données marketing.
• 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
• Eagerness to develop: you actively grow your skills, seek feedback, and treat new tools and methods as opportunities rather than threats
• 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
• Proficiency in Python for analysis, modeling, and automation
• Strong analytical track record: someone who has measurably influenced business or marketing decisions through analysis, not just produced reports
• 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
• Statistical foundation: experimentation, significance testing, regression, segmentation, forecasting, and the judgment to know which applies
• Solid SQL. You can independently query, join, and explore data without waiting for someone to prepare it for you
• Proactivity and autonomy: you raise your hand early, plan your own work, and look for impact without being asked
• Strong communication and stakeholder skills: you can challenge weak measurement respectfully and make a recommendation, not just present options