In a nutshell
Within Sainsburys Argos we have an amazing asset in our customer and digital data. Our overall strategy includes maximising the business value from this asset and to do so, we are recruiting a Data Scientist who will use advanced analytical and mathematical techniques to provide insight into our customer behaviour from this asset.
As a Data Scientist within CMI, you will be working on a number of business problems or opportunities, understanding what actions we can take to acquire and retain more customers, model, optimise and predict the behaviour of customers from our marketing campaigns and create models to understand the value we obtain from these campaigns. You will be using data from the entire business, selecting the appropriate techniques and models best suited to solving the questions and ultimately deploying models to allow us to maximise our revenue.
Whilst this role is at the heart of Marketing and will be primarily solving marketing based problems, this role will be collaborating across Sainsburys Argos and Sainsburys Group, building out our Data Science capability and therefore you can expect to work on problems from all business areas over time
What you need to do
This role will be working on a number of projects and will be required to:
With support from the Senior Data Scientist, select appropriate and apply advanced analytical techniques to perform statistical analyses, create predictive and prescriptive models on customer behaviour.
Research analytical options, design features, prototype and test algorithms.
Work with the IT Machine Learning Engineers and digital marketers to operationalise solutions
Engage with a wide range of Marketing stakeholders to understand business issues and opportunities to apply Data Science techniques to drive tangible benefits. Explain clearly to non-technical audiences how the techniques and models answer the business questions
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 work with our data management teams to allow them to improve understanding of the business performance
Perform ad-hoc analyses and presenting results in a clear manner
How I will succeed
Delivering solutions to real business problems that otherwise the organisation would have been blind to. Sharing your expertise and knowledge with the business to build meaningful models and analysis that is translatable into clear actions and benefits for the organisation. Collaboration with the Analytical and insights teams, IT teams and the marketing department to understand business problems, build and embed analytical solutions.
What I need to know
Likely to have an 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 predictive customer modelling and econometric modelling within a retail environment is an advantage
What I need to show
Passion for data and business improvement
Curiosity and research mindset: eager to look for new technology, algorithms and data that could be used to improve our business
Problem solving skills: generate hypotheses, design experiments, test hypotheses, build models
Good communication, presentation and facilitation skills. Ability to explain complex concepts in understandable ways, effective Data visualisation for clear story telling
Work quickly and accurately under pressure, eager to learn, develop and progress
Resources available to me
A vibrant team to bounce ideas with and to support you with specialised knowledge. An emerging Data Science community across Argos and the Sainsbury’s group.
An Engineering team creating an in-house Big Data and Machine Learning infrastructure (Data Lake, Hadoop/Hive, Spark, Python, etc.) making the operationalisation of large predictive and prescriptive model possible.
Mentoring and coaching from members of the team who have deep business and data knowledge as well as Data Science and technical knowledge (Python, R, SPSS)
What decisions I can make
Selection of the appropriate techniques and methods to answer business problems, presentation of recommendations to the business based on the data and analysis.
You can also make decisions on any platform, programmes or analytics tools or styles.