Lead - Data Scientist

Job Description

Job Summary Lead customer analytics and personalization initiatives using Azure AI services and large-scale customer data platforms. Key Responsibilities Design and deploy machine learning models using Azure Machine Learning for customer segmentation, churn prediction, lifetime value estimation, and recommendation systems. Analyze historical customer data to uncover behavioral patterns and actionable insights. Build and optimize recommendation engines using collaborative, content-based, and hybrid approaches. Develop and evaluate targeted marketing campaigns using predictive analytics and personalization strategies. Operationalize ML workflows using Azure MLOps (CI/CD, model versioning, monitoring, retraining). Collaborate with data engineering to build scalable data pipelines using Azure Data Factory and Azure Synapse Analytics. Integrate models with real-time systems using Azure Functions, Event Grid, and API Management. Present insights and model outcomes to stakeholders through dashboards and storytelling using Power BI. Required Skills / Must-Have Technical Skills: Python, SQL, scikit-learn, XGBoost, TensorFlow, PyTorch Azure Services: Azure Machine Learning, Azure Synapse Analytics, Azure Data Factory, Azure Cognitive Services, Azure Functions & Logic Apps, Azure Experience: 5+ years in data science with focus on customer analytics and personalization Platforms: Customer Data Platforms (Adobe Experience Platform, Salesforce CDP, Segment) MLOps Tools: MLflow, Azure ML Pipelines, DVC Data Warehousing: Snowflake or equivalent Statistical Methods: A/B testing, causal inference, statistical modeling Nice-to-Have / Preferred Skills Industry Experience: Airline, travel, or retail industry Architecture: Real-time personalization and event-driven architectures using Azure Event Hubs or Kafka Deployment: FastAPI or Flask integrated with Azure API Management Education & Qualifications Primary Education: Bachelor?s or Master?s degree in Computer Science, Statistics, Mathematics, or related field Secondary / Acceptable Alternatives Education Preferred: Bachelor?s in Engineering or equivalent with relevant experience in customer analytics Secondary: Master?s in Data Science or AI Certifications/Licenses Azure AI Engineer Associate (preferred) Azure Data Scientist Associate (preferred) MLflow or DVC certification (preferred) Skills Grouping & Synonyms Customer Analytics: Customer segmentation / churn prediction / LTV modeling Recommendation Systems: Collaborative filtering / content-based / hybrid Azure AI: Azure ML / Synapse / Data Factory / Cognitive Services MLOps: CI/CD / model monitoring / retraining / ML pipelines Real-time Systems: Azure Functions / Event Grid / API Management