Lead / Senior Data Scientist - Retail Promotion Optimization
Join a global retail leader to optimize its primary growth driver: promotions. In an international context, you will design and enhance sales forecasting models, measure the true incrementality of promotional campaigns, and translate complex business challenges into actionable data solutions. This strategic role requires expertise in Python, SQL, and Google Cloud Platform to directly impact financial performance and operational efficiency.
Responsibilities:
Design and improve sales forecasting models to predict the impact of each promotion.
Develop methods to measure incrementality, cannibalization, and other side effects.
Contribute to the optimization stream to allocate financial gains to priority investments.
Translate specific business problems from Merchandise and other departments into data solutions.
Ensure the successful industrialization and delivery of models into a modern cloud environment.
We are seeking a Lead/Senior Data Scientist to join a strategic team at a global retail leader. The mission is to revolutionize the management of the promotional catalog across several European countries. You will tackle the challenge of optimizing the entire lifecycle of promotions, from product selection to measuring real-world impact. The goal is to drive financial performance (margin, revenue) while navigating complex logistical constraints and customer behaviors like cannibalization and stockpiling.
Requirements:
5+ years of experience in Data Science (mandatory).
Proven experience in the Retail or CPG sector (mandatory).
Experience with sales forecasting, assortment, or promotion optimization.
A business-first mindset with the ability to explain results to non-technical stakeholders.
Expertise in incremental measurement, price elasticity, and saturation effects.
Technical stack: Google Cloud Platform (GCP), BigQuery, Python (expert), SQL, Kubernetes (K8S).
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