Data and Machine Learning Engineer

Last updated 12 days ago
Location:West Midlands

Description

Data and Machine Learning Engineer - 0000ED75

The WPB UK Data and Analytics department provides actionable insight that drives the business forward. As the business moves from data rich to data driven, using machine learning (ML) and artificial intelligence (AI), the Data and Analytics team are central to driving this transformation. The department provides ML, AI, management information dashboards and visualisations which are used to measure and improve the performance of the business. In addition, the team is at the centre of customer intelligence and marketing; using ML to communicate the right message, to the right customer, at the right time.

The Data and ML Operations squad is part of the Data and Analytics department, which builds, automates and maintains the core data and ML products for the organisation. These products are the basis for machine learning, AI and visualisation services. The team build and maintain the data model, data catalogue, data lineage and manage data quality for the organization. The team is working on two strategic programmes to adopt Google Cloud Platform (GCP), open source technologies and agile methodologies.

The Data and ML Engineer will work closely with teams across Data and Analytics and HOST to deliver a stable platform on which data and analytics products and services can be developed at pace and with quality. Ensure that everything is automated and instrumented so that the environment is controlled and governed is an efficient and effective way.

Key responsibilities are:

  • Transforming data and analytical product and operational requirements into solutions
  • Represent the Data and Analytics team to drive the delivery of the data and analytics platform in GCP
  • Design, develop, and deploy the data and analytics pipelines that power the Data and Analytics team deliveries
  • Drive the automation and instrumentation of data and analytics pipelines
  • Monitor, maintain and troubleshoot issues in the data and analytical pipelines and data environment