We're currently seeking a knowledgeable data enthusiast to join Morrisons' Supply Chain Performance, Data and Insight team. As part of a fast paced retail environment, you’ll be working closely with both the Data Modelling and Insight teams to help provide our supply chain with important data to help keep the nation fed. The Supply Chain team touches nearly every aspect of our operations, including:
- Availability and Waste - making sure we've enough stock at the right time, balancing with the amount that goes to waste
- Ranging and merchandising - making sure we've the right mix of products available to customers
- Logistics optimisation - smoothing out peaks and troughs in demand for our warehouses, delivery depots, manufacturing sites and suppliers
- End-to-End efficiency - touching every aspect of the journey from farms and manufacturing sites right through to the till
In your day-to-day role you will spend most of your time working in Python and Google Big Query so knowledge of Python or R is preferable and some experience of programming is essential. You'll be expected to have some experience with data visualisation, preferably building dashboards. Knowledge of Data Science techniques is required for the role but not essential at the outset because training will be provided on the job, so if you’re looking to transition from a software development or data engineering role then you’re in the right place. Some of your duties will include:
- Be a point of knowledge using data to answer key questions within the business, such as:
How many sales did we miss due to not having enough stock of an item?
Which products could we remove from our range?
What is the optimal delivery frequency for stores to balance cost and product availability?
- Using our state-of-the-art data facilities in GCP to extract, transform and load data (ETL) for the data science team
- Supporting the data science team with data and basic modelling tasks including:
Building feature sets for modelling tasks
Productionising machine learning models in the cloud
Building basic models such as forecasting sales and waste across the estate
Building dashboards in google data studio and Qlik