Most large retail corporations will have several big departments or sections where a good understanding of mathematics is required and used. Below is a summary of some of these. Some companies might group these differently but the basic functions will operate somewhere in the business.
If you want to get into banking and finance then working in a finance department for a large commercial organisation could be of interest. Finance Departments work on financial models that underpin many activities in the organisation. For example, they will work out how to calculate various profit margins which take into account a range of fixed and variable costs. Different margins will be used by different parts of the business depending on the reporting reason. Some large retailers have graduate schemes which are specifically tailored to finance. Retail finance might be appealing if you like working on practical problems which are linked to the fast-paced world of retail.
Operations looks after the general operation of the business. Operations managers have to be able to make good business decisions based on data and other information. Mathematical decision making, and other areas of operational research and a good understanding of statistics and data are important here.
As well as understanding the cost and effect of marketing and advertising campaigns, marketing departments need people who can analyse website data, for example by studying what is in a consumer basket, or looking at patterns in website clicks. They might then apply machine learning algorithms in order to target advertising campaigns and future buying and selling strategies.
Trading and commercial
The trading department will use mathematicians to look at ordering of goods and pricing. This involves negotiating with suppliers for the best price, working out supplier discounts and includes discounting end of lines. The price of items is important in order to maximise profit and minimise loss that might occur through over ordering.
Companies have teams of analysts (either in one large department or dispersed within other departments) to analyse data. This can be as simple as working out the average spend of customers to working out new and innovative statistical models to forecast demand. You might see jobs advertised with titles like Data Analyst or Data Scientist. It is worth reading job descriptions carefully, as Data Analyst roles can vary a lot in terms of complexity, with some roles being more mathematical than others.
Some Data Scientists will be expected to have a PhD and experience with techniques such as machine learning. The demand for this type of person is only set to grow. Spend a few minutes googling ‘data scientist retail jobs’ and you will get a flavour of what is out there.
Supply Chain and Logistics
Mathematicians and operational researchers work in the supply chain side of a commercial organisation to help improve the distribution of goods getting from suppliers to customers via stores or online sales and deliveries. This process can be optimised in various ways and thus mathematicians and operational researchers are necessary to implement the most suitable optimisation algorithms for the specific situation.
What should I do next if I am interested in retail?
Does it excite you?
Firstly, think about whether you are excited by the fast paced world of retail. Are you the kind of person who is always analysing instore promotions, or trying to work out why your supermarket has changed the layout of their store? If you are constantly thinking of how to do things better when you walk round a supermarket, then retail could be for you.
Are you an entrepreneur?
If buying/selling really interests you, double check that you aren’t actually destined to be an entrepreneur. Plenty of maths graduates have an entrepreneurial spirit which leads them to set up their own businesses. On the other hand, there are lots of people who get some experience first before branching out.
How specialised do you want to be?
How much higher-level maths do you want to do as part of your job? This is an important question to ask yourself. For example, if a maths graduate works in Logistics, they won’t all be using advanced maths on a daily basis. They will however constantly be using their problem-solving skills, and analytical brain to tackle real world problems. For many types of maths graduate this will be extremely satisfying and interesting. If on the other hand you want to be working in a more mathematical area, then you need to investigate the specialisms which allow this.
Do you need further study or qualifications?
If you want to become a data scientist, operational researcher or statistician, then you might need to complete some further study before entering the world of work. It is also more and more likely that you will need to become a competent programmer, although many people learn this on the job. If you like the idea of further study then you will also be leaving your options open, as professionals in these areas could work in a number of different sectors including retail, healthcare, government and so forth.
Do some investigation
Make sure you get talking to companies at graduate fairs – attend presentations and find out as much as you can. Start trawling the graduate recruitment pages, as well as the general job sites. Remember that careers fair representatives might not all be familiar with the most technical roles such as data scientist – you might need to do some more digging.
Get some experience
Work experience and summer internships are all going to help give you a head start when it comes to getting a job in retail. It will also give you an idea about whether the culture and working environment are right for you. Any retail work experience, such as working on tills or stacking shelves is useful. It will give you a much better idea about how a retail business works and make you much more employable.
Don’t neglect your ‘soft’ skills
Don’t forget your soft skills – leadership, communication, working in a team and so on. Some retail graduate schemes can be extremely competitive so you need to be able to sell yourself. Even if you are a data scientist, you still need to be able to communicate with your colleagues in a way which they can understand. Make sure you focus on these soft skills as much as your technical skills.