You come from either an Engineering or Data Science background, with a good understanding of the Data Science Toolkit (Programming, Machine Learning, MLOps etc) and bringing data science solutions into production. You therefore tick the majority of the following points:

Key Requirements:

A higher degree in engineering, computer science, maths or science.
Customer focus with the right balance between outcome delivery and technical excellence.The ability to apply technical skills and know-how to solving real world business problems.
Demonstrable experience of building MLOps systems according to the best market standards.
Commercial experience contributing to the success of high impact Data Science projects within complex organisations.
Awareness of emerging MLOps practices and tooling would be an advantage e.g. feature stores and model lifecycle management.
knowledge of ML workflow/orchestration platform like Airflow
An analytical mind set and the ability to tackle specific business problems.
Experience with different programming languages and a good grasp of at least one language. The ideal candidate is fluent in Python.
Use of version control (Git) and related software lifecycle tooling.
Experience with tooling for monitoring, logging and alerting e.g. Splunk or Grafana.
Understanding of common data structures and algorithms.
Experience working with open-source Data-Science environments.
Knowledge of open source big-data technologies such as Apache Spark.
Experience building solutions that run in the cloud, ideally Azure.
Experience with software development methodologies including Scrum & Kanban.
A background or strong understanding of the retail sector, logistics and/or ecommerce would be advantageous but is not required.

Unsure if you fit all the criteria? Apply and give us the chance to evaluate your potential – you could be the perfect fit!