It was a big culture shock for me when I realised what big data really was – having the ability to process terabytes of data on a cluster in a matter of seconds.by Imran Khan
I first joined Vodafone as an intern in the Big Data team back in February 2017. This was as part of my MSc in Data Science at King's College London where I collaborated with Vodafone to conduct a research project. Prior to that I studied physics at Imperial College. As a result of the internship, I was lucky enough to be offered a full-time job and I've been with Vodafone since where I joined a fantastic group of highly intelligent colleagues from whom I've learnt so much.
It can be quite daunting if you're at university and considering entering the exciting world of data science or technology in general. In this blog I'll focus on the three main differences, as I see it, between what you’re perhaps going through now as university students and working in a corporate environment and how Vodafone as a company helps you make that transition.
Your work at university takes place in a somewhat closed, self-contained environment. You'll be working in relatively small groups on toy problems with little impact on the outside world. At Vodafone, I work in large, globally distributed teams to build models to deploy across numerous markets which have an impact on millions of our customers. Data science is becoming central to Vodafone's operations in terms of everything from running marketing campaigns to optimising our cellular network.
Size of data and tools
At university you might only be using data that can stored on your computer. It was a big culture shock for me when I realised what big data really was – having the ability to process terabytes of data on a cluster in a matter of seconds. We also use an array of tools – it's not just Python and SQL but also Spark, Hadoop, Git etc.
Attitude toward failure
In certain situations, failing at university can have some pretty bad consequences. At Vodafone, failing and experimentation is encouraged – you don't have to be an expert from day one. When I first started, I couldn't write production quality code, I barely knew how to use the command line and version control was completely foreign to me. We invest time and resources in your education and well-being. For example, you might be enrolled in a training course on deep learning or discussing the latest research trends in a reading group.