Meet People Working in Data Science – Online Careers Panel Session
Our panelists:
On February 27th Dr Helen Giles, Dr Joanne Kenney, and Dr Paul Agapow joined us to share their experiences of moving from academia into data science and IT consultancy careers. A huge thank you is in order to our panellists for sharing their time, expertise, and personal experiences. It was an inspiring and motivating evening! Here are some highlights from their advice and experience:
Joanne started off by reflecting on how, in the early days as a Neuroscientist and thinking about a career change, the word “industry” was bandied about by people, but it was a “black box”. She encouraged us to ask the question, “What does it really mean ‘industry’?” As we learned from all 3 panellists, networking with people is one of the most important ways to open up the black box of industry and discover what it could mean for us. Joanne recommended a classic Planned Happenstance approach: keep trying things out – all of your experiences will accumulate, you will discover things you didn’t know existed all the while adding to your skills, expertise, and network.
More specifically related to her move into data science, Joanne shared how it took a while to learn how to do an industry specific CV, learning how to translate her research gained skills into a language an industry employer could easily understand. She reached out to various people, and was even invited in to visit a company. Joanne recommended Linkedin as a helpful tool in research and networking, and a way of perhaps finding a mentor to support you in your transition. Once you’ve done your research – IF you need to upskill, there are plenty of online courses that can help you. (Ed. Including Data Upskilling Courses here at the Bayes Centre).
Helen moved from Astronomy to industry at the end of a post-doc in Germany, only just managing to get back to the UK before the pandemic. In her words, she “had to stop and think about what to do next”, and the importance of self-reflection, understanding our wider life priorities and needs, and netowrking were themes throughout Helen’s talk.
She knew how to work with data, enjoyed writing papers, and organising (and like helping people be organised). Academic publishing seemed a possibility for awhile, but as Helen did her research into the sector, talked to people, and continued to self-reflect, it turned out not to be a preferred option. She stressed the importance of evaluating job descriptions, she spoke with someone she knew doing data science to gain insights but her 1st interview didn’t go to plan!
Helen shared her experiences of autism and job seeking, noting that her first non-academic interview was difficult, partly because the employer was not able to support neurodivergent candidates. Her friend suggested she use recruitment consultancy instead and that strategy worked. Now works with a range of clients on specific working with diverse projects involving new data, new techniques, coding and producing document reports.
Paul started his presentation off by noting whatever we plan, “the world takes you off in different directions”: it could be HE, it could be consulting, it could be, government, it could be some other industry. You can find Paul’s slides on How to make every mistake and still have a career on Slideshare. Like Helen and Joanne, Paul stressed how being proactive is the foundation of luck – use your network for advice, information, and as a sounding board – do not wait for the right job to appear.
Paul acknowledged, companies can be suspicious of those that have worked in academia for a long time, more than 1 postdoc you might be viewed as too academic. The tendency in academia to polish things to 90% but in business if you can get a good enough answer then that is good enough! You need to be aware of a more structured way of working, the senior boss has the responsibility to contact other teams not you. In industry you are less attached to projects than academia.
You have to prove you can adapt to a business enterprise and be practical. Again, networking is super important – get on LinkedIn and link to other people – get people in your own network to introduce you. Try to have fun with Linked In & Twitter.
Some other important insights:
- Be kind to yourself
- Don’t apply for everything – “a soft search is the best way to start” – so restrict yourself to one day per week
- Careers are not straight lines – don’t feel bad for moving after 2 years (you can advance more and learn more if you move around
- Allow yourself to be lucky (i.e., proactive)
- Be the person that solves problems – you will be valued for this
If you are thinking of a career transition, you can book a 1:1 consultation with Eleanor Hennige or Darcey Gillie to discuss plans, options, strategies, and more.
