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
