Operations research and analytics postgraduate personal statement example

Personal statement example

My interest in operations research began with a timetabling problem that had nothing to do with mathematics lectures. I help organise a volunteer football coaching group, and every autumn we struggle to fit twelve coaches, four age groups and two pitches into three evenings a week. For two seasons we did it with a whiteboard and argument. In my second year I wrote out the constraints properly, treated it as an assignment problem and solved it in a spreadsheet solver. The schedule was not perfect, but it was produced in an hour rather than a fortnight, and it made me see that the mathematics I enjoyed most was the kind that had to survive contact with people's preferences.

My degree gave me the foundations for that. I took linear algebra and optimisation, statistical modelling and stochastic processes, and I chose a final-year project on appointment scheduling at a community clinic. Working from anonymised aggregate arrival and consultation data that the practice manager was willing to share, I built an M/G/1-style queueing approximation and then a discrete-event simulation in Python using SimPy. The comparison was the most useful part of the work: the analytical model was tidy but assumed stationary arrivals, while the simulation let me test what happened when late arrivals clustered after school finishing times. I found that grouping longer appointments at the end of a session reduced simulated average waiting time more reliably than simply shortening slot lengths, though the result was sensitive to how often patients did not attend. Writing the discussion taught me to be candid about the limits of a model built on limited data, and I was pleased that my supervisor's main criticism was about presentation rather than method.

Since graduating I have worked three days a week as a scheduling assistant for a bakery that delivers to around forty cafés and shops. My job is mostly practical: confirming orders, adjusting van loads and rerouting when a driver is ill. It has been an education in the difference between an optimal route and an acceptable one. Two of our drivers know their areas well enough to beat the software on timing, and one customer insists on a delivery window that makes the rest of the round awkward. I have started keeping a simple record of late deliveries by day and route, and the pattern that emerged, consistent Friday delays on the longest round, was enough to persuade my manager to split it. I am aware that this is descriptive work rather than analytics, and that is part of why I want to study further: I can see where forecasting and vehicle routing methods would help, but I cannot yet implement them at a standard I would trust for a business decision.

Alongside work I share care of my younger brother, which has made me methodical about planning my time and comfortable with revising plans when they fail. I read around the subject in the gaps, most recently Bertsimas and Tsitsiklis on linear optimisation, which I am working through slowly because the duality chapters repay rereading, and I have been teaching myself Julia for solver work after using mainly Python and R.

From a master's I want rigorous grounding in integer programming and stochastic modelling, more experience with large-scale solvers, and a dissertation with a genuine client problem behind it, ideally in logistics or healthcare capacity. In the longer term I would like to work as an analyst in a team that sits close to operations, where the modelling is judged by whether the schedule holds on a Friday afternoon.