Description

Lead the design, development, and production deployment of machine learning models that drive prediction, risk detection, and decision support.

This role is hybrid.

Responsibilities

• Build, train, validate, and optimize ML models for scoring, prioritization, and engagement.
• Develop scalable feature pipelines and reusable datasets using structured and semi-structured data.
• Manage the full ML lifecycle including monitoring, drift detection, retraining, and versioning.
• Translate complex business requirements into production-ready ML solutions and measurable outcomes.
• Ensure engineering best practices through testing, documentation, and reproducibility.

Required Skills

• 5+ years of hands-on machine learning model development.
• 3+ years of production ML deployment and operational support.
• Strong proficiency in Python and SQL.
• Experience with Spark, Databricks, MLflow, and Snowflake.
• Cloud platform experience (Azure, AWS, or similar).
• Hands-on expertise with scikit-learn, XGBoost, and modern ML libraries.
• Deep understanding of MLOps, feature engineering, and model validation.

Preferred Skills

• Experience with Generative AI and AI automation.
• Background in predictive modeling, scorecards, and decisioning systems.

Key Skills

Education

Bachelor's degree