Description

Own the end-to-end lifecycle of machine learning models, from prototype to production deployment and monitoring.

This role is hybrid.

Responsibilities

• Develop and maintain production-grade Python code with modularization, testing, and performance tuning.
• Design, build, and deploy scalable ML pipelines using Databricks and Azure.
• Execute data extraction, cleaning, and analysis to support statistical and machine learning techniques.
• Implement model orchestration, monitoring, and optimization in production environments.

Required Skills

• Master's or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, or related quantitative discipline.
• Strong Python expertise for data engineering and machine learning.
• Hands-on experience with ML pipeline development and productionization.
• Experience with Databricks, Spark-based ML pipelines, and Azure cloud platforms.
• Proficiency in SQL and working with large-scale datasets.
• Knowledge of ML lifecycle tools such as MLflow, CI/CD, and model monitoring.
• Minimum 3 years of experience in a quantitative or technical professional environment.

Preferred Skills

• 8+ years of technical professional experience.
• Experience with data visualization tools like Tableau or PowerBI.
• Domain knowledge in the airline industry or consulting roles.

Key Skills

Education

Master's degree