Argos is building its own Data Science and Machine Learning capability, aiming to automate and improve the millions of decisions that we need to make daily to provide great availability of products to our customers across multiple fulfilment propositions and at a competitive price.
Argos Supply operation accounts for over 40,000 lines, multiple sales channels, over 1000 suppliers, 800+ stores, 10+ distribution centres and global sourcing. For us, Machine learning is not buzz words, with senior level commitment the business is giving this real focus as the key to fixing problems within our supply chain.
As a Data Scientist in the Commercial Supply function, you will join a team building predictive and prescriptive models to optimise commercial supply trade-offs, specifically but not limited to demand forecast, store assortment, inventory and customer service. So, if you can source, extract and prepare data, test algorithms and be passionate in your search for data solutions. This could be the perfect role for you!
As a Data Scientist, your main responsibilities will be:
Apply advanced analytical techniques to perform statistical analyses, create predictive and prescriptive models
Research analytical options, design features, prototype and test algorithms to create solutions to supply chain problems
Work and build strong working relationships with the IT Machine Learning Engineers to operationalise solutions
Engage with a wide range of Commercial Supply stakeholders (e.g. Merchandisers, Merchandise Managers, Supply Operational Managers) to understand business issues and opportunities to apply Data Science techniques to drive tangible benefits
Help the organisation understand the principles and the maths behind Data Science to drive buy-in of the analytical solutions being developed
Proactively acquire data from various sources and analyse it to improve understanding of the business performance
Perform ad-hoc analyses and presenting results in a clear manner
What do you need to know?
MSc or PhD in relevant subject (mathematics, physics, statistics, econometrics, operational research, computer science or related fields)
Strong experience in quantitative research and analytics
Able to find solutions to loosely defined business problems leveraging complex data
Experienced in database querying (e.g. Microsoft SQL) and performing statistical analyses on large data sets of very sparse data (e.g. at store/SKU level over multiple time periods – 17 million data points per period – where 85% of stocked products sell less than one unit per store per week)
Practical experience in using data mining and machine learning techniques (e.g. linear regression, logistics regression, decision trees algorithms, clustering, neural networks)
Strong programming skills (at least one of Python, R, Hadoop or equivalent)
Business experience of retail merchandising and supply chain optimisation (including demand forecasting, stock optimisation, assortment planning, range optimisation, pricing and markdown optimisation)
What you’ll get in return:
As well as the usual company benefits, which include, 24 days holiday, save as you earn scheme, discretionary annual bonus and company pension scheme, you will work in an exciting environment with the potential to develop your skills for a career that fits with your own aspirations.