Senior Data Scientist – Intelligent Media Targeting

As a Senior Data Scientist – Intelligent Media Targeting, you will play a key role in designing and deploying advanced customer analytics and marketing science solutions that enable intelligent media planning and customer targeting. You will work on customer segmentation, Marketing Mix Modeling (MMM), causal measurement, marketing effectiveness, and AI-powered analytics to help global clients optimize media investments and drive measurable business outcomes.

This role requires strong expertise in machine learning, statistical modeling, customer analytics, and marketing measurement, along with the ability to translate complex analytical findings into actionable business recommendations. You will collaborate closely with business stakeholders, data engineers, and cross-functional teams to deliver scalable, production-ready data science solutions.

Key Responsibilities

• Design and develop advanced customer segmentation models using clustering techniques such as K-Means, GMM, DBSCAN, or similar algorithms.
• Build and deploy Marketing Mix Models (MMM) to measure marketing effectiveness and optimize media investments.
• Engineer customer and transaction-level features including RFM, spend trajectory, recency decay, and behavioral metrics.
• Develop statistical and machine learning models for customer targeting, campaign optimization, and marketing effectiveness measurement.
• Perform causal inference, experimentation, and A/B testing to measure incremental impact of marketing initiatives.
• Apply model explainability techniques such as SHAP to generate meaningful business insights and customer narratives.
• Develop reusable Python-based analytics frameworks and scalable machine learning workflows.
• Partner with business stakeholders to understand marketing objectives and translate them into analytical solutions.
• Present analytical findings and strategic recommendations to business and leadership teams.
• Collaborate with data engineering teams to build scalable data pipelines and production-ready analytics solutions.
• Contribute to AI-enabled analytics initiatives by leveraging Generative AI, LLMs, or AI-assisted workflows where applicable.
• Mentor junior team members and contribute to analytics best practices and reusable frameworks.