Senior ML Data Scientist: End-to-End ML on Azure

CTC; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

CTC is seeking a highly skilled ML Data Scientist to lead design, development, and deployment of machine learning solutions. This business-facing role partners with stakeholders to translate challenges into scalable ML products using Python and Azure Databricks ML.

You will build end-to-end pipelines, analyze large datasets for actionable insights, monitor models, and collaborate with data engineering and analytics teams to deliver production-ready solutions, with a focus on ML lifecycle

Qualifications

• 7+ years of experience in Data Science and Machine Learning.
• Strong expertise in ML model design, development, and deployment.
• Hands-on experience with Python and ML frameworks/libraries.
• Extensive experience with Azure Databricks ML, MLflow, and Azure cloud services.
• Strong understanding of statistical modeling, predictive analytics, and MLOps concepts.
• Excellent communication skills with the ability to interact effectively with business stakeholders.

Responsibilities

• Work directly with business users to gather requirements and identify ML-driven opportunities.
• Design, develop, train, validate, and deploy machine learning models.
• Build and optimize scalable ML pipelines using Python and Azure Databricks.
• Analyze large datasets to generate actionable business insights.
• Monitor model performance and implement improvements as needed.
• Collaborate with data engineering and analytics teams to deliver production-ready solutions.

Skills

ML model design

Python

Azure Databricks ML

MLflow

Azure cloud services

ML lifecycle management

Statistical modeling

Business stakeholder communication

Generative AI

NLP

Tools

Azure Databricks

Job description

CTC is seeking a highly skilled ML Data Scientist to lead design, development, and deployment of machine learning solutions. This business-facing role partners with stakeholders to translate challenges into scalable ML products using Python and Azure Databricks ML.

You will build end-to-end pipelines, analyze large datasets for actionable insights, monitor models, and collaborate with data engineering and analytics teams to deliver production-ready solutions, with a focus on ML lifecycle