Data Science Architect

Data Science Architect

Posted 1 week ago by Response Informatics

Apply
Negotiable
Undetermined
Undetermined
London Area, United Kingdom
Apply
Artificial Intelligence AWS SageMaker Data Science Lifecycle Management Machine Learning Management Microsoft Azure Python (Programming Language) PyTorch (Machine Learning Library) Scikit-learn (Machine Learning Library) SQL (Programming Language) TensorFlow

Summary: The Data Science Architect role requires a seasoned professional with 6–10 years of experience in data science and analytics leadership. The position emphasizes expertise in model lifecycle management and MLOps, alongside strong analytical and communication skills. The candidate will be responsible for assessing and designing processes for data science delivery and model management. This role is based in the London Area, United Kingdom.

Key Responsibilities:

  • Lead applied data science initiatives and analytics leadership.
  • Manage model lifecycle and experimentation frameworks.
  • Oversee data science governance and organizational processes.
  • Utilize MLOps concepts and tooling effectively.
  • Employ data science tools and languages such as Python, R, and SQL.
  • Synthesize technical observations into actionable business recommendations.

Key Skills:

  • 6–10 years of experience in applied data science or analytics leadership.
  • Strong understanding of model lifecycle management and experimentation frameworks.
  • Familiarity with MLOps concepts and tools (e.g., MLflow, Kubeflow).
  • Hands-on experience with Python, R, SQL, and relevant frameworks.
  • Excellent analytical and communication skills.

Salary (Rate): undetermined

City: London Area

Country: United Kingdom

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: Other

Detailed Description From Employer:

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.
Apply
Similar Jobs
Loading data...