Purpose of the Role:
You will leverage our data foundation to design, build, and deploy machine learning models that create tangible business value. You will move beyond dashboards and reporting to develop predictive and prescriptive analytics capabilities from the ground up.

Key Responsibilities:

• Model Development: Build, train, validate, and deploy machine learning models to solve key business problems (e.g., forecasting, churn prediction, recommendation systems).
• MLOps & Infrastructure: Establish and maintain the MLOps infrastructure for model versioning, monitoring, and continuous integration.
• Data Collaboration: Work closely with data engineers to define data requirements for modeling and ensure the availability of clean, feature-ready data.
• Feature Engineering: Analyze and transform raw data into effective features for model training.
• Prototype to Production: Translate proof-of-concept models into robust, scalable, and production-ready solutions.
• Stakeholder Alignment: Collaborate with business leaders to identify AI opportunities, define success metrics, and integrate model outputs into business processes.