Sheffield, England, United Kingdom
I am an ambitious and motivated mathematics graduate, with a range of experience with different technologies and excellent analytic, communication and literacy skills, who is keen on finding good solutions to hard problems. I have had a couple of years of industry experience with Java and Scala, principally working on learning algorithms and optimization systems on both Windows- and Unix-based systems, feeding in data acquired from databases using SQL and HiveQL, and analysing results using R and spreadsheets (Excel and OpenOffice). I have also had university experience with C++, HTML, MATLAB/Octave and Maple, as well as working on my own small coding projects in all of these languages. I am also familiar with a wide variety of mathematical areas, such as number theory, group theory, graph theory, automata theory, differential geometry, topology and functional analysis.
Working in the recommendations team, I have built recommendation engines for multiple purposes. I am also in charge of ML Ops as well as sharing my knowledge with other/junior members of the team.
Principally worked on supply chain analysis, including optimising for multiple objectives and measuring the impact of extreme weather conditions.
Recommender systems, including the product alternatives (which you can see under Or How About These) and the Get The Look for the Tu lines on Argos.
In this role, I worked principally on predicting delivery windows for parcels. Initially I joined an existing project, where my main role was to turn a Python prototype into a more scalable version by translating it into Scala and implementing some of the processes in Spark. Later, I created a prototype using a different approach that would let us take into account more of the variables we discovered impacted delivery times. This required collating data from a variety of sources, and getting a good idea of the inconsistencies between them as well as their own issues. It also required providing reports on progress to feed back to Operations on a daily basis, as well as provide information to senior stakeholders. I have also worked on a range of smaller projects, including: applying business rules alongside product recommendations, and detecting delivery points receiving regular high quantities of mail based on differing rule sets for different purposes. The main languages I used in this role were Python and Scala, using Teradata SQL to access data. I also worked somewhat with Excel to provide reports with detailed data on various projects.