We are looking for a Data Scientist to join our Data Team, focusing on driving Campaign Excellence, Retail Media insights, and Loyalty initiatives through data science and machine learning. You will play a key role in transforming complex business needs into data-driven solutions, from building end-to-end pipelines in Azure Databricks to delivering insights that enhance customer engagement and business performance.
Key Responsibilities
- Collaborate with marketing, CRM, and retail media teams to translate business requirements into technical data science solutions.
- Design and implement end-to-end data pipelines from data ingestion, cleaning, and feature engineering to model deployment using Azure Databricks and MLflow.
- Develop and optimize audience segmentation and targeting models for campaign activation and personalization (e.g., behavioral clustering, propensity scoring).
- Build and maintain RFM and loyalty scoring models to drive customer retention, cross-sell, and upsell strategies.
- Communicate findings effectively to non-technical business stakeholders through storytelling, visualizations, and dashboards (e.g., Power BI).
- Monitor model performance, conduct A / B tests, and continuously improve campaign impact and personalization strategies.
- Document models, workflows, and results following best practices for reproducibility and governance.
Key Qualifications
3+ years of professional experience as a Data Scientist or Machine Learning Engineer.Proficiency in Python, SQL, and frameworks such as scikit-learn, pandas, and NumPy.Strong hands‑on experience with Azure Databricks, PySpark, and MLflow for data processing and model lifecycle management or similar tools is a plus.Understanding of loyalty models (RFM, CLV, churn prediction) and their application in customer engagement.Proven experience in end‑to‑end machine learning workflows from data preparation to production deployment.Strong ability to translate business challenges into analytical solutions and explain technical results to non‑technical audiences.Familiarity with Power BI or similar tools for insight visualization and stakeholder communication.Seniority Level
Mid‑Senior levelEmployment Type
Full‑timeJob Function
Information TechnologyIndustries
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