Job title: Machine Learning Engineer
Locations: Manchester or Haywards Heath (hybrid working)
Role overview
Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.
Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.
As a Machine Learning Engineer, you will help build and maintain the pricing team s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.
Key Responsibilities:
- Build an MLOps / DevOps environment to support machine learning automation
- Build the pipelines that automate the regular model update and monitoring processes
- Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
- Work closely with the data science team to integrate modelling approaches and techniques
Key Skills and Experience:
- Previous experience as a DevOps / MLOps engineer
- Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
- Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling from the ground-up, not only through the use of packages and libraries
- Proficient at communicating results in a concise manner both verbally and written
- Previous industry experience in a STEM role or educated to the Master s level in a STEM or DS / ML / AI or maths-based discipline.
Behaviours:
- Collaborative and team player
- Logical thinker with a professional and positive attitude
- Passion to innovate and improve processes
- Strong grasp of industry standards, and proficient in either Python, R, or both