This started out as an experimental journey… I had already transitioned from music to teaching to SAP consulting. Would it be possible for the next leg of the journey to take me into the world of data science? At the outset I was not at all sure, but in the spirit of taking a sho’t left, I made a start, just to see what would happen… I figured at the very least a little intellectual stimulation could do a person no harm.

It all started with one of those clichéd life-changing experiences – a little brush with cancer that got me asking long-overdue questions like ‘what do I want to be when I grow up?’ and ‘how could I find meaning and purpose in my work?’. I thought about the things I love doing and allowed myself to dream about possible new careers. And the more I looked at data science, the more fascinated I became! One day, sitting on the couch at home, I found myself signing up for my first online Python course (still thinking in the back of my mind ‘this is ridiculous…’). But that is the wonderful thing about the abundance of online learning platforms available: you can try stuff out with relatively little to lose. I didn’t have to give up my job or enrol at a university: I just had to begin and see if it led anywhere. And it did! By the time I read about the IBM/MTN rhino conservation project (whose inspirational work really cemented my decision to take this journey seriously), I’d been coding and brushing up on math and finding any way I could to apply my new skills at work – even if just to automate repetitive tasks that I found a bit tedious.

A major milestone came in October 2018 when I was accepted onto the 2-month full-time Data Science Intensive program in Cape Town – what a joy to spend the whole day grappling with machine learning problems, together with like-minded colleagues. At the same time, it was also tough: impostor syndrome is a very real phenomenon and there were nights when I’d lie awake thinking ‘maybe I’m just kidding myself…’. But then there was the excitement of figuring out how to make a small piece of code work, or the greater delight in seeing a model actually make valid predictions. Wow!

Back at work, I was keen to move into my new chosen field – because by now there was no doubt in my mind that data science was for me. I started networking within my own company because I knew from experience that networking is often the fastest route to a job, compared with more traditional job-hunting methods. I approached the data team and basically asked if there was anything I could help with (willing to work for free after-hours was my ‘impossible to refuse’ pitch!). I was given my first assignment in December 2018 and my family had to endure me rushing home from Christmas lunch so I could carry on with my EDA… luckily they are an understanding and supportive bunch of people.

A couple of months later this same team had a resignation and I was invited to a technical interview to assess my SQL skills and fitness for the job of data analyst. This must have gone well because suddenly my foot was in the door and I had my first job offer: granted, as a data analyst rather than a data scientist BUT it came with the understanding that there would be plenty of scope to use and develop my data science skills. And indeed in 2020 I was given the opportunity to move into a data science position permanently and I grabbed it with open arms.

The funny thing is that at this point in the story I feel like I should be writing something like ‘I had arrived!’. But, with data science being what it is, the more you know the more you realise you need to know. And of course it’s such a fast-moving field so there are new things to learn on a daily basis. And so the next leg of my journey began when I enrolled for an MSc in Data Science at the University of London. I chose the University of London for 2 reasons: I needed the flexibility to study online while I continued working full-time; and unlike many other institutions they accept candidates who may have a Bachelor of Music(!) but can prove sufficient prior learning in data science concepts to justify acceptance into the programme.

Completing the MSc programme has been a tough 3½ years, but I have no regrets: my knowledge has broadened and deepened in so many areas and I also found my passion: natural language processing. My final thesis was on the topic ‘Automatic knowledge graph construction from news articles’. Of course it’s only been 6 weeks since I submitted and already I find myself thinking ‘What’s next?’ So onwards and upwards… 😆 (but only after a nap or two please!).

The one thing I really want to highlight about this journey is that I have not at any point travelled alone. Bruce Bassett was one of my first mentors. I remember sitting in a café with him back in 2017 wondering aloud whether I should even entertain thoughts of becoming a data scientist. He said to me ‘If you’re comfortable with being uncomfortable a lot of the time then this could be for you’. He was not wrong! Some days it feels like a blessing to be out of my depth because it means I’m learning new skills, but other days the struggle is real! Mark Barrett was my line manager when I started out, and (can you believe?) actually gave me time and space to pursue this interest, and introduced me to people in Media24 that could help me in the quest. Gareth Lloyd was one such person: the one who took me up on my offer to do some work on the side, eventually gave me that first opportunity as a data analyst, and then saw to it that I was promoted into a data science role. The head of HR, Shelagh Goodwin, also (to my surprise and delight!) took me seriously when I approached her for advice on how to do this career wiggle and introduced me to several useful contacts immediately. And finally I need to mention Tobie Vermeulen: it feels like he has been my personal champion on this journey – but actually I think it’s just his nature: all his staff feel the genuine interest and care there. He made sure, together with Andreij Horn and Mark Barrett that I was given a chance to transition, and then made sure that I had all the resources I needed to complete my studies. When I read this list (and this is just the short version), I feel I have been most fortunate indeed.

24.com also wrote an article on My journey from SAP specialist to data scientist.