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 :

- Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or related field.

Secondary / Acceptable Alternatives Education :

Preferred :

- Bachelors in Engineering or equivalent with relevant experience in customer analytics.

Secondary :

- Masters 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.