Job - Senior ML Ops Engineer | MBN
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Senior ML Ops Engineer

  • Data Science
  • Edinburgh
  • Permanent
  • £85,000
  • #44857
  • About the role

    Senior ML Ops Engineer – Edinburgh (Fully Remote)

    Up to £85,000 + Package

    Join as a Data Scientist in the Machine Learning Operations Team

    • This is an opportunity to achieve excellent exposure in a challenging role and to make an impact when projects reach Deployment and start to deliver real value for customers 
    • You’ll be joining ML Ops as an SME to work with large, complex data sets to solve difficult, non-routine analysis problems, applying your own choice of advanced analytical methods using the latest Data Science tools
    • You’ll also be managing both new and existing Machine Learning Pipelines on-premise and migrating to cloud
    • You will promoting excellence across the lifecycle of Model Validation & Risk, Monitoring & Retraining, Technical Assurance, CICD and adoption of new techniques
    • We’ll look to you as a Thought Leader to actively participate in the data community, supporting the bank’s strategic direction through better use of data

    What you'll do

    As a Data Scientist in MLOps, you’ll be supporting the business to improve business processes and products with scientific rigor. You’ll be collaborating with multi-disciplinary teams of data engineers and analysts on a wide range of business problems including the prevention of financial crime, understanding customer interactions with the bank and the management of credit risk.

    The skills you'll need

    • Experience developing ML Pipelines with modular components such as versioning, tracking and reporting
    • Solid understanding of Software Engineering principles with a particular focus on CI/CD implementation
    • Full stack deployment experience ideally through a cloud platform such as AWS Sagemaker or through containerised methods such as Kubernetes and Docker
    • Experience of Data Engineering excellence particularly in regard to python, spark and pipeline development
    • Experience of platform management and pipeline optimisation is desirable
    • The ability to demonstrate leadership, self-direction and a willingness to both teach others and learn new techniques
    • Extensive relevant work experience, including expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models and sampling methods


    For more information or to apply, please send an updated CV to or apply now.