While remote working has many benefits, one of the challenges for new data scientists can be making the transition from academia to the workforce.
Managing this transition was challenging before but the new ways of working have added to the complexity, where people used to be able to pick up a lot of knowledge by osmosis or looking over the shoulder of their colleagues, now it’s done through video calls or Slack.
So, with that in mind, here are our top five tips for emerging data scientists to help grow their careers.
Data science is a huge field. No-one (particularly at entry level!) is expected to know everything. Choose the discipline (machine learning, data visualisation, analytics, etc) that you most enjoy or excel at and focus all on a job that allows you to upskill in this area quickly. The more you do, the more you’ll learn. A focused discipline approach will allow you to practice in an area you understand intuitively, freeing up thinking time to learn new approaches and techniques.
You have to consider that in the fast-moving domain of data science, you’re unlikely to ever be finished with learning. In fact, many data science industry experts are of the view that learning only really begins when (full time) academia ends. Continue to absorb everything you can in new advances in the field, research papers, approaches, challenges, etc. While you can’t know everything, you’ll be viewed as a data science expert in your organisation, so immerse yourself in knowledge and learn as much as you can about the wider industry.
You will transition far more rapidly into commercial organisations, and progress faster within them, if you get what the business is about. Understand structure, hierarchies, products, processes, people and politics (with a small ‘p’). You never know when your data science skills will be required by someone from a different part of the business to the area that you usually work with, so make sure you can quickly absorb domain expertise at the same pace as you absorb discipline expertise and broader data science expertise.
The most effective data scientists understand the value they had to the business, how they fit within it and what they can do for it. An engrained understanding of how business works will help you stand out from the crowd.
Being able to effectively engage with less technical colleagues from sales, HR, product, marketing and finance teams will help you transition into, and thrive, in a business world.
Other departments will most likely have very little understanding of the nuances of your profession, so you’ll need to be able to explain what you do in a way that’s clear, understandable and approachable. Learn how to negotiate, present, collaborate, share, consult and listen carefully to the needs of your less-technical colleagues.
Keep in touch with former student colleagues, course leaders, researchers, academics and anyone who has been part of your academic career. Expect to regularly contact them to ask for advice, guidance, explanations and support.
Data science, as a field, has a strong connection to academia so nurture and cultivate the relationships that you have built on a long-term basis. Once you start working commercially, maintain exactly the same approach to cultivating your professional networks.
You never know when you will need to ask for help or advice so make sure to look after your network and use it frequently!
A great way to start building your network and getting involved in the data science community is to join one of our regular events.