remoteonsite
Data Scientist - MLOps Manager - EY
Data Scientist
Lead a high‑impact MLOps team, designing and deploying scalable machine learning pipelines on AWS, Docker, and Kubernetes, while driving data science initiatives and ensuring production reliability.
About the role
Key Responsibilities
- Architect, develop, and maintain end‑to‑end MLOps pipelines for large‑scale data science projects.
- Collaborate with data scientists to translate models into production‑ready services using Python, Docker, and Kubernetes.
- Implement CI/CD workflows, monitoring, and observability for ML models in AWS environments.
- Lead a cross‑functional team, mentoring engineers and fostering best practices in model governance and reproducibility.
- Partner with stakeholders to define performance metrics, data quality standards, and deployment strategies.
Requirements
- 6–10+ years of experience in data science and MLOps, with a proven track record of deploying ML models at scale.
- Strong proficiency in Python, AWS services (SageMaker, ECS, EKS), Docker, and Kubernetes.
- Experience with CI/CD pipelines, monitoring tools, and model versioning systems.
- Excellent communication skills and ability to lead technical teams.
- Knowledge of data governance, security, and compliance best practices.
Skills
mlopsmachine learningpythonawsdockerkubernetes