Data Scientist

Your Role & Impact

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We are looking for a skilled Data Scientist to join our team and lead the development of automated analytics, customer data solutions, and cloud/clean room environments.

In this role, you will be instrumental in delivering and scaling high-impact initiatives such as Multi-Touch Attribution (MTA), full-funnel measurement, Customer Lifetime Value (CLV) modeling, propensity scoring, CRM measurement frameworks, and Customer 360 solutions.

The ideal candidate will bridge the gap between data science, customer data engineering, and marketing technology.

You will automate data wrangling across AdServer, Website, CRM, Loyalty, and Customer Data Platform (CDP) ecosystems, enabling advanced audience activation, personalization, and measurement in a privacy-first environment.

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What will you do:

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• Data Integration & Wrangling: Gather and clean data from various sources, including local databases, cloud platforms, and clean rooms. You will automate the integration of AdServer, Website, and CRM data to ensure accuracy and scalability.
• MarTech & CRM Technology Solutions: Support the implementation and integration of CRM and marketing automation platforms; define data flows, audience synchronization processes, and technical requirements; ensure seamless data activation across channels.
• Advanced Analytics & Productization: Develop proprietary metrics and easy-to use analytics products. Your goal is to create reusable tools that improve media efficiency and customer targeting across multiple clients
• Predictive Modeling: Build and maintain machine learning models (e.g., Random Forests, Gradient Boosting) for forecasting, advanced user segmentation, and ROI focused attribution.
• Strategic Optimization: Work closely with strategy and planning teams to translate complex findings into actionable recommendations that drive campaign performance.
• Solution Architecture & Technical Consulting: Translate business and marketing requirements into scalable data and MarTech solutions. Create technical documentation, data flow diagrams, integration specifications, and solution recommendations.
• Automation & NLP: Deploy web scrapers, automation workflows, and NLP models to streamline data collection, insight generation, and customer intelligence processes.