Description

Key Responsibilities
✔ Build, train, validate, deploy, and optimize machine learning models for prediction, scoring, decision support, prioritization, engagement, and risk detection.
✔ Perform exploratory data analysis, feature engineering, model training, evaluation, calibration, monitoring, retraining, and lifecycle management.
✔ Develop scalable and production-ready ML solutions balancing performance, explainability, maintainability, and business value.
✔ Build reusable datasets and feature pipelines using structured and semi-structured data.
✔ Collaborate with business stakeholders to translate complex requirements into practical ML solutions and measurable outcomes.
✔ Lead rapid prototyping and production implementation using modern AI and data platforms.
✔ Provide technical leadership while ensuring engineering best practices including testing, versioning, documentation, and reproducibility.
🔹 Required Skills & Experience
✅ 5+ years of hands-on Machine Learning model development.
✅ 3+ years of production ML deployment and operational support experience.
✅ Strong expertise in Python and SQL.
✅ Experience with Spark, Databricks, MLflow, Snowflake, Azure, AWS, or similar cloud platforms.
✅ Hands-on experience with scikit-learn, XGBoost, and modern ML libraries.
✅ Strong understanding of feature engineering, model validation, monitoring, drift detection, retraining, and MLOps.
✅ Ability to communicate complex ML concepts effectively to both technical and business stakeholders.
⭐ Preferred Expertise
✔ Production ML & MLOps
✔ Predictive Modeling & Scorecards
✔ Scoring & Decisioning Systems
✔ Generative AI & AI Automation
✔ Product Development & Rapid Prototyping
✔ Stakeholder Management & Requirement Shaping

Key Skills

Education

Bachelor's degree