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Data Scientist ML Ops

  • Data Science
  • Edinburgh
  • Permanent
  • £70,001-£80,000
  • About the role


    Data Scientist (Machine Learning Operations) Edinburgh (Fully Remote)

    Up to £75,000 + 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, youll be supporting Commercial D&A to improve business processes and products with scientific rigor. Youll 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.


    Youll also be:

    • Developing and deepening your knowledge of data structures and metrics, advocating for change where needed for product development
    • Developing frameworks to promote coding standards, data quality, scalability and Ethical AI
    • Communicating effectively across the functions and franchises to make business recommendations, gaining business buy-in to solutions tailored to customers need
    • Identifying new methods, tools, techniques and opportunities to deliver business value via cost reduction, income generation or improved customer experience through the application of data science


    The skills you'll need

    • Experience with statistical software, database languages, big data technologies and cloud environments
    • Experience of Big 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.