Case study

Trainee consulting analyst — Ravi

A curious mind, the desire to problem-solve and meet challenges head on are ideal for a career in data analysis

How did you get your data analyst job?

After realising how much I enjoyed interpreting and visualising data I also discovered that I liked reporting and explaining my analysis.

I followed the football analytics community on Twitter and witnessing others doing such interesting work lead me to collect data to see what I could find out about my favourite football team. My mind was made up - I wanted to not only be a data analyst, but one who worked with, created and presented data visualisations.

I was lucky to find the perfect role through a job advertisement on the Information Lab on Twitter. The role offered training in working with data and data visualization and the chance to work in a dynamic team. The interview process had two stages: first, we had to find some interesting data and create a visualisation in Tableau, then present it in a 30-minute video interview.

If you got to the final interview stage, all candidates were then given the same dataset, and had to prepare a visualisation for a 15-minute presentation, and take part in a 15-minute competency interview.

What's a typical working day like?

I commute to London so I use the time on the train to read up on blogs or articles I may have missed or to do some data analysis of my own.

I'm usually with a client for six months, on long-term or short-term projects, or both. I could be presenting projects, running tutorials or training sessions or developing internal content (wikis, blogs, how to guides).

The variety of project work is really appealing to me. Scoping the project, trying, iterating and developing a report or visualisation, to help solve business problems, is really engaging. It's a job where you can use both logical and creative skills.

What do you enjoy about your job?

I love storytelling and making an impact. The field of data is so diverse that there are so many insights and gains to be made from effective use of data. Being able to uncover trends and patterns to answer questions is fantastic.

What are the challenges?

Getting lost in the data. Sometimes you can have the biggest data table, and have no idea where to start, so scoping the task and understanding the data in front of you is important. Being able to recognise the fields to use, the questions to ask and the approach to take is vital before you've even started.

Roadblocks to analytical freedom are also a challenge. Many firms are content where they are, and a challenge can be to help show them that there are other ways of looking at, and analysing, their data.

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