Data Science Architect

Qualifications

• 6–10 years of experience in applied data science, machine learning, or analytics leadership.

• Strong understanding of model lifecycle management, experimentation frameworks, and data science governance.

• Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML).

• Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

• Proven ability to assess or design organizational processes for data science delivery and model management.

• Excellent analytical and communication skills, with the ability to synthesize technical observations into actionable business recommendations.