Senior Account Manager - Data Science

Job Description:

Data Scientist

Role Summary

Join a team that builds the intelligence layer powering Dentsu's measurement and marketing science capability. You will support the development and deployment of MMM, incrementality, and forecasting models that get operationalized as scalable, agentic solutions. This role combines rigorous statistical methodology with a product orientation.

Key Responsibilities

• Support development of marketing mix models (MMM), incrementality analyses, and forecasting models using Bayesian methods and Meridian
• Prepare and validate data for 3rd Party Agentic Analytics client pilots, ensuring data quality and completeness for model inputs
• Build and maintain model pipelines that are reproducible, documented, and ready for productization
• Collaborate with Senior Data Scientists on model validation, calibration, and client-ready output generation
• Create data visualizations and model output summaries for client-facing deliverables
• Work with the AI Agents team to package models as agentic, low-cost-to-run solutions
• Document methodologies, assumptions, and model limitations for internal and client audiences
• Support Media Effectiveness teams with model interpretation and training materials

Required Qualifications

• 2+ years of experience in data science, applied statistics, or quantitative marketing
• Strong foundation in statistics, regression analysis, and causal inference
• Proficiency in Python (pandas, scikit-learn, stats models) and SQL
• Experience with Bayesian modeling frameworks (PyMC, Meridian, or similar)
• Understanding of marketing measurement concepts (attribution, incrementality, media mix)
• Comfort working with large, messy real-world datasets
• Strong written communication skills for documenting methodology and results
• Ability to work independently across time zones with an onshore lead

Preferred Qualifications

• Experience with Google Meridian or similar open-source MMM frameworks
• Exposure to media/advertising data and campaign analytics
• Experience deploying models via APIs or automated pipelines
• Familiarity with Databricks or cloud-based ML platforms
• Experience creating training materials or enablement documentation

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