Data Scientist – Revenue Management & Cloud ML

About the role

We are seeking a Data Scientist with deep expertise in revenue management and cloud‑based machine‑learning operations. The role focuses on turning complex business problems into scalable analytical solutions that run reliably in production environments.

Key responsibilities

• Design, develop, and deploy revenue management models and algorithms.
• Implement end‑to‑end MLOps pipelines within enterprise CI/CD frameworks.
• Build and maintain ML APIs on Google Cloud Platform (GKE) and leverage Vertex AI, BigQuery, and Dataflow/Dataproc for data processing.
• Configure infrastructure as code using Terraform and container technologies.
• Set up model monitoring, autoscaling, and feature‑store integrations to ensure production stability.

Required profile

• Advanced degree in Statistics, Operations Research, Computer Science, Mathematics, or Machine Learning.
• At least four years of hands‑on experience with cloud ML deployment, MLOps, and revenue‑management modeling.
• Proven ability to apply statistical and machine‑learning techniques to real‑world problems.

Required skills

• Programming: Python, R, SQL, TensorFlow, PySpark, Java, JavaScript, C++.
• Machine‑learning techniques: clustering, decision‑tree learning, artificial neural networks.
• Statistical methods: regression, distribution analysis, hypothesis testing.
• Cloud platforms: GCP, GKE, Vertex AI, BigQuery.
• Infrastructure: Terraform, Docker/Kubernetes containers.
• Data processing: GCP Dataflow, Dataproc.
• MLOps: CI/CD pipelines, model monitoring, autoscaling, Feature Store, Artifact Registry, Analytics Hub.