How do we make our data science career programme work remotely?

The Faculty Fellowship is designed to give aspiring STEM PhD and masters graduates a chance to make a smooth transition from academia into commercial data science. By the end of 2019, we had that process down to a fine art. 

And, like almost everyone else, that fine art was put under incredible strain in 2020. 

With the entire nation working from home, we had to ask ourselves a vital question: how could we recreate the same capability building, soft skills training and real world experience in a virtual format?

We didn’t want to just ‘make it work’ and scrape by. We wanted to seize this chance to add more value, forge deeper relationships and really show our fellows and host companies that AI projects can create real results, even when they’re delivered virtually. 

We took a number of steps to ensure that our virtual data science training and remote work placements continued to deliver real value – steps that we’ll take again as we continue to run virtual fellowships throughout the first half of 2021. 

Shift the ratio of fellows to mentors

Mentorship from Faculty’s commercial and technical teams is essential for our fellows; these partnerships give them the chance to request support, solicit feedback and ask questions on everything from business norms to client relationships and tricky machine learning problems. 

Anyone who’s been working from home for the last year knows that everything takes longer when you’re doing it remotely; meetings, decisions, planning sessions and even project updates can often end up slowed down by anything from missed Slack messages to wifi issues. 

On the other hand, we knew that not having the ability to turn to a neighbour and ask questions, listen in on important conversations, or just forge relationships in the office kitchen meant that our fellows would need regular, formalised support from their Faculty mentors more than ever. 

So we made the decision to accept fewer applicants, so that mentors from commercial and technical teams had the space and time to give our fellows the attention they deserved. 

Reinvest the time won back from commuting

Many of our fellows never set foot inside the offices of their host companies, though they spent six weeks working closely alongside them to get data science projects up and running. That meant, of course, that some of the impromptu learnings and exposure to professional norms that comes from seeing how commercial businesses function first-hand was lost – but our fellows gained something, too. 

Less time spent on commuting meant, for some fellows, an extra hour available each day. We wanted to make the most of that time. 

Making data science work in the real world means working with real, diverse teams in a professional environment, so training in ‘soft’ skills like public speaking and writing has always been a major component of the Faculty Fellowship. This year, we used the first half hour of every day – the hour that would have been spent getting into work on foot, on a train or in a car – on a new series of in-depth training and development sessions. 

Together, we connected to deliver additional skills training on the areas where fellows felt they needed a little extra support – everything from impromptu public speaking to writing, active listening and professional development. 

Make a conscious effort to bring fellows together

As many of us have discovered this year, it’s easy to lose connections with coworkers when you’re only ever connected via a screen. 

But camaraderie has always been a vital component of the Faculty Fellowship – many of our fellows meet on the programme and, over eight weeks, form professional and social bonds that they retain for years afterwards. We weren’t willing to let go of that. 

Early on, when regulations allowed, we managed to meet one another for socially distanced Friday dinners in groups of six. When restrictions tightened, we met virtually on Friday evenings for games nights, chatted over our morning training sessions, and kept in touch over Slack. 

Large video calls aren’t great for encouraging casual conversation, so we also split the fellows into smaller ‘hubs’ of four or five people. These hubs gave the fellows a closer support network that allowed them to form deeper relationships; under their own steam, we soon saw these groups organising virtual lunches, socially distanced walks, bike rides and other social occasions where they could ‘talk tech’ and share their experiences. 

The fellows reported that, while they can’t wait to see their colleagues in the flesh one day, these activities were vital in building and maintaining a support network and sense of community.

Embrace the benefits of remote events

Demo Day is the flagship event of the Faculty Fellowship: one evening during which our fellows can present the results of their projects before an audience to host companies, Faculty team members and leading voices in the commercial data science community. It’s during Demo Day that many of our fellows get the chance to network and make vital contacts – many of which lead to their first permanent full time jobs in data science. 

Again, networking isn’t easy over video call. But holding a virtual Demo Day yielded some surprising positives. For one thing, the lack of seating restrictions meant that we were able to throw our (virtual) doors wide to the whole data science community, providing fellows with an unprecedented range of networking opportunities. In fact, it was our most attended Demo Day ever, with 387 attendees.

Now, even the most experienced speaker might quail at delivering a lecture before that many people, but once again the virtual format delivered unexpected benefits; when fellows had the chance to present virtually, from the comfort of their own homes, they reported that they felt significantly more relaxed and poised to speak about their work with the pride that these projects deserve. 

Want to take the next step in your data science career?

All these activities and interactions have allowed us to become a highly collaborative and high performing team that has supported, interacted, argued, laughed, helped one another and bonded in a very special way. Beyond that, we’ve all learned how to survive and thrive in a fully virtual world – both personally and professionally. 

If you’re a STEM masters or PhD graduate who’d like to take the next step from academia into a career in data science, find about more about the Faculty Fellowship.