Description

You will build and deploy end-to-end machine learning pipelines within a Databricks environment.

This role is remote.

Responsibilities

• Design and deploy predictive models for forecasting, churn analysis, and fraud detection.
• Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, and deployment.
• Optimize model performance using hyperparameter tuning, AutoML, and MLflow tracking.
• Collaborate with engineering teams to operationalize models via batch/real-time processes using Databricks Jobs or REST APIs.
• Implement Delta Lake for scalable, ACID-compliant data workflows and enable CI/CD using Databricks Repos and GitHub Actions.

Required Skills

• 5+ years of experience in data science or related roles.
• Proficiency in Python and SQL.
• Hands-on experience with Spark and Spark MLlib.
• Experience building and managing pipelines on Databricks.
• Knowledge of AutoML and MLflow.
• Experience with GitHub and GitHub Actions for CI/CD.
• Ability to work with REST APIs.
• Competency in troubleshooting Spark jobs and Databricks environments.

Preferred Skills

• Bachelor’s degree in Computer Science, Statistics, or a related field.

Key Skills

Education

Any Gradute