Lead AI Feature Engineer

Create and maintain reusable, production-grade feature data products improving machine learning performance across multiple Danaher operating companies.

Design and execute feature engineering and selection experiments from complex scientific and enterprise data to maximize model performance and reliability.

Establish best practices for feature quality, lineage, monitoring, and lifecycle management to ensure scalable and production-ready AI solutions.

Strong hands-on experience in data science, machine learning, feature engineering, and predictive modeling.

Proficiency in Python, SQL, machine learning libraries, and modern data-processing frameworks for operationalizing ML solutions.

Experience building scalable data pipelines and feature generation workflows in cloud-based environments.

Work Experience Required: Not explicitly mentioned in the JD.

Experienced in developing reusable feature stores or feature engineering frameworks across multiple ML solutions.

Background in predictive modeling techniques such as gradient boosting, ensemble methods, Bayesian modeling, or advanced statistical approaches.

Exposure to life sciences, diagnostics, healthcare, laboratory, or other data-rich scientific industries.