How to Build a Data Science Network

4 minute read

Networking as a terminology is all over the place. If googled, it results in about 553,000,000 found entries. Whilst most of them will be about telecommunication, all but one of the results on the first page cover the type of networking, we are talking about – business networking. Everyone seems to agree how important networking is for career development. Asked, what is the best recommendation for how to find a new job was, one recruiter recently answered: “Networking.” Asked, how do I do this in a new professional field in a new city; he fell silent.

Merriam Webster defines “networking” as “the exchange of information or services among individuals, groups, or institutions; specifically: the cultivation of productive relationships for employment or business”.

So how do you start a professional network from scratch?

I recently came to London to participate in a data science bootcamp run by Pivigo called S2DS (Science 2 Data Science), a 5-week intensive programme to transition academics into industry data science roles. As everyone from the S2DS cohort, I have recently been facing several big changes in my (professional) life. We are all about to leave academia and transition to industry. Additionally, many of us are physicists, astronomers, mathematicians, software-engineers and many other backgrounds but have not necessarily been mingling intensively with the data science community before. In my personal case (and similar to a few others on the course) I have also moved after my PhD starting my life in a new city and a new country.

So, whilst my professional academic physics network was well-developed before S2DS, my professional data-science network consisted of not more than a handful of loose contacts, which I had met at several data-science related meet-up events. Not very promising for “cultivating productive relationships for employment and business” in a new field. And I am not alone with this problem. When facing the challenge of moving from academia to industry, we often face a lack of peer-support, not necessarily due to the lack of support, but due to the lack of peers.

And this is where S2DS comes in. What was I expecting of S2DS? Certainly a large group of highly-skilled, highly-motivated people, all eager to become data-scientists, working in teams and exchanging knowledge about data-science subjects. What have I found? Exactly that. But also so much more. First-of-all, what I found was a group of people with similar ideas about academia and industry as I had. Everyone I spoke to, loved academia for one reason or the other and everyone had done brilliant work beforehand. But everyone for one reason or the other also thought, that it was by now time to seek new challenges and opportunities. And coming from a field of academia, where most people decide to stay and hang-on, so meeting people with a similar drive to change their ways was refreshingly comforting.

Secondly, of course, not everything is about psychological comfort only. Gathering over 90 people together in one place who have similar aspirations for five weeks produces great dynamics. In addition to having lots of fun and bonding moments, we formed groups, helped each other with CV writing and coding, revised each other’s cover letters and looked for job adverts together. Everyone is back home by now, but if I need somebody for a second opinion on a piece of code/CV/cover letter/… I know, whom to contact and will not hesitate to do so (in fact, one of the other fellows even kindly agreed to proof-read this blog post).

Thirdly, as mentioned before, not everyone on the course was from London. Myself and a few others are based in Edinburgh, which I have always felt is a bit under-served with data-science events. We now know enough people up here (and know them well enough) to start organising events (meet-ups, talks, learning-groups, Kaggle-competitions) on our own. So many things that we now have a critical mass for (BTW: if you are reading

But we should not forget the valuable networking opportunities outside of the 2016 London cohort. As part of S2DS, Pivigo organised a set of industry viewpoint lectures, where they invited data scientists to present their work and their companies. Afterwards there was time for questions and chatting. Through this, we were able to get in contact with a lot of interesting companies and get to know people already working in the business. Additionally, they organised an evening event, where they also invited the alumni of previous years, so we could get to know each other. Lots of fantastic opportunities to meet like-minded people in the field of data-science and to grow one’s network even more.

All-in-all I am really happy having attended S2DS. I managed to grow my data-science network from about a handful to between 100 and 150 people all already working or going to be working in data-science all over the UK and Europe (and some even in places as far as Mexico). And one of the nice things about networking is that once, you have a critical mass, everything becomes easier.

So, Happy networking ahead!

This blog post was originally published on the S2DS alumni blog. You can find it here.

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