Description

Build, deploy, and maintain machine learning models and data pipelines using ML-DevOps frameworks.

This role is remote.

Responsibilities

• Deploy statistical and ML models via established ML-DevOps pipelines.
• Develop and evaluate ML solutions for predictive maintenance use cases.
• Perform root cause analysis on production outages using causal inference.
• Identify new data science opportunities by collaborating with IT and business teams.
• Apply quantitative analysis to solve complex data problems.

Required Skills

• 8+ years of experience in data science or quantitative analysis.
• Strong proficiency in Python and SQL.
• Hands-on experience with AWS and GCP BigQuery.
• Practical knowledge of ML-DevOps workflows.
• Experience with PyTorch, TensorFlow, and Scikit-learn.
• Proficiency in data modeling and predictive modeling.
• Experience with Databricks MLFlow, AWS SageMaker, Kubeflow, or Azure ML.
• Ability to use PowerBI for data visualization.

Preferred Skills

• Experience with modern cloud-based data science platforms.
• Background in natural language processing or artificial intelligence.

Key Skills

Education

Any Gradute