Senior Data Scientist - ML Engineering & MLOps

About the role

Roche is seeking a Senior Data Scientist to lead end‑to‑end machine‑learning production systems within the Global Analytics and Technology Center of Excellence (GATE). You will own the full MLOps lifecycle, from model development to scalable cloud‑native deployment, supporting Roche affiliates worldwide.

Key responsibilities

• Architect, deploy and maintain cloud‑native ML pipelines, containerized services and orchestration tools (Airflow/Dagster) with strict performance and cost SLAs.
• Design reusable MLOps platform components such as feature stores, model registries, experiment tracking, and automated CI/CD pipelines using GitLab CI or GitHub Actions.
• Build automated back‑testing, drift detection and observability frameworks to monitor model accuracy, data quality and performance decay.
• Provide technical leadership through code reviews, refactoring research code, and mentoring data scientists on production‑grade software practices.
• Collaborate with global affiliate teams to explain model outputs, gather business requirements and incorporate feedback into roadmaps.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics or a related quantitative field.
• 7+ years of experience operating and maintaining machine‑learning systems in production.
• Current residence in Costa Rica or valid work authorization for San José.

Required skills

• Python, Linux/Bash, SQL.
• Data pipeline tools: Spark, dbt, Snowflake, Databricks.
• Containerization and orchestration: Docker, Kubernetes, Airflow.
• MLOps tools: MLflow, Weights & Biases, GitLab CI, GitHub Actions.
• Cloud platforms: AWS, Azure, GCP.
• Machine‑learning frameworks: scikit‑learn, XGBoost, PyTorch, TensorFlow.