When your networking is driven by curiosity rather than asking for a job, I found people were very receptive to that. It didn’t come off as needy… or creepy!
- Talking to someone in the bathroom at a conference
- Striking up a conversation with a fellow passenger on a flight
- Catching up with a primary school friend via LinkedIn
No, I’m not listing the world’s least effective dating strategies… these are all genuine ways in which I’ve known people find their first jobs after finishing postgrad degrees. Yes, that’s right… cover your ears… I’m about to drone on about the power of networking. Having worked with hundreds of PhD researchers over the past few years, I’ve often seen this power in action. But never had I seen it in quite so eloquent a way as when I stumbled upon this visualisation one day on LinkedIn:
Look again.
In her transition from academia to working in data science, Kinga Stryszowska-Hill had only gone and created a Sankey chart plotting which job hunting methods had led her to actual interviews and job offers. Cue immediate screenshot.
Out of a total of 57 job ‘applications,’ only one of the 42 made through an online application portal had led to an actual interview. A 2.4% interview rate. For jobs uncovered through networking, that increased to a staggering 90%, including two job offers. These figures left even me, the networking fairy herself, somewhat speechless. I needed to know more about how Kinga had done it, and to share her methods with the PhD world.
So, in the true spirit of networking, I reached out to her, and we had a great conversation about how she made her transition from academia to data science. Here are the highlights… *BEWARE* … serious nuggets are to be found within.
Kinga began by filling me in on her academic background in wetland ecosystems and landscape ecology. After a string of fixed-term academic contracts and several years trailing her husband and daughters around the USA in search of her next position, she decided a change was needed. It was the lack of a guarantee of steady, long-term position that pushed me to look elsewhere, she explained.
In the early stages of exploring possible next steps, Kinga joined the Professor is Out Facebook Group: a group in which people who are looking to make, or have recently made, the transition from academia into other sectors share their anxieties, tips and experiences. The group is curated by none other than author of the seminal The Professor is In, Karen Kelsky, PhD. It was there that Kinga was introduced to the idea of working in Data Science.
I just decided to start doing some informational interviews with people in the field, says Kinga. This wasn’t as part of a deliberate job search, but just to learn more about the field. She began with an existing contact she had come across in academia who was now working as a data scientist for US government. He then connected her to another data scientist… and so the conversation web started. I just talked to people who did the types of roles I was interested in, she adds. The actual job search at that point in time wasn’t a priority, as I still had a whole year left on my postdoc. I just wanted to explore, build up my CV, and just gauge people’s interest in me as a candidate.
This approach of coming from a place of curiosity paid dividends. When your networking is driven by curiosity rather than asking for a job, I found people were very receptive to that. It didn’t come off as needy… or creepy! she points out.
So, how else did Kinga help herself to take the #awks out of ‘networking?’ One things she did was to reach out to people who might typically hire people into roles she wanted, but who weren’t currently advertising:
I thought, hiring managers are the ones who can tell you what they look for in an employee Kinga explains. I identified them by searching for ‘data analytics manager’ or ‘data science manager’ on LinkedIn and pinging them a connection request, saying that I was interested in transitioning from PhD to data analytics or data science, and I was keen to learn more about their priorities when hiring. I also asked them questions including whether they were interested in hiring someone with a PhD. Importantly, these weren’t people who were currently hiring, they were just people with experience of hiring for such positions… So it wasn’t like asking for a job!
In all, her networking led Kinga to having over 50 conversations with people working in the fields of data analytics and data science. The real thing I wanted to know though was how those conversations wound up in two concrete job offers.
The first came through narrowing my search to environmental companies, because they matched my background and my values, Kinga explains. Looking too broadly was overwhelming, so that focus helped. I found one company where one of my friends was working, albeit in a totally unrelated role. So, I connected to a few other people in the company working in data-related roles and had conversations with them; I also pinged a connection request to a recruiter saying I had a background in ecology, was interested in data analytics, and I’d love to learn more about any upcoming positions.
A few months later, the recruiter posted on LinkedIn that they were expanding their data analytics group. I then reached out to him, only for him to reply asking for my CV to send to the hiring manager! There were no specific positions advertised, it was just a general announcement that they were growing their analytics team. The hiring manager liked my CV so much he created a position for me!
Wow. The dream! And what about the second job offer?
This one came from Googling around for environmental start-ups Kinga says. I found an interesting company and tried to connect with their CEO on LinkedIn, but she ignored my connection request. From there, I connected with a data analyst in the company who accepted, and we had a good conversation about her work. She said they were hiring, which otherwise I wouldn’t have known because small companies like this one often don’t post job adverts because they have so few resources to invest in advertising. She showed me how to apply, which I did… and and got the job!
So this time, it was only through this exploratory conversation that Kinga found out there was an opening.
As a long-time advocate for the powers of networking, even I was taken aback by how effective this had been for Kinga. She had gone from not even understanding the differences between data analytics and data science to a choice of two job offers in five months. So what takeaways can we get from her story to see how networking can actually work in helping the transition from academia to other sectors?
1. Make the most of online communities
More than ever, people are mobilising to create virtual communities of folks looking to move beyond academia, or who have already made career moves. Kinga used The Professor is Out group on Facebook to look at advice being shared and to gather suggestions for possible alternative careers. Other groups include AltAc Careers UK and GradGrid. Join these kinds of groups, explore stories, and don’t be afraid to ask for help and ideas.
2. Start conversations early
If we think about the job hunt as a series of conversations, it’s best to start them at a point when you can come from a place of curiosity and conversation rather than from a place of ‘needing a job.’ Kinga had a whole year left on her postdoc when she started her career options ‘research project,’ which allowed her to come from a place of curiosity, not one of scarcity and need.
3. Play the ‘long game’ – sow some seeds
Set up conversations with people who hire into the roles you want… not because they are hiring at that moment, but because you want to learn from their perspective for when the time comes. It’s like sowing seeds that will shoot up months down the line, as they did for Kinga with her first job offer. And how do you identify these potential hiring managers, I hear you ask? For Kinga, it was simply through adding ‘manager’ in front of the role, e.g. ‘research manager’, ‘data science manager,’ and using these terms to perform a people search on LinkedIn.
Also, like Kinga did, follow recruiters on LinkedIn. You’ll then be the first to know when opportunities arise. Kinga saw a post mentioning that a company was expanding their data team; this wasn’t even a formal job advert, and she wouldn’t have seen the opening and made an approach if she hadn’t been following that recruiter on LinkedIn. Curate your feed to make sure opportunities find you. And how do you identify recruiters? If you look up a company on LinkedIn, then go to ‘people,’ then scroll across and select ‘Human Resources’ from the ‘What they do’ option… look for anyone with ‘talent acquisition’ or ‘recruitment’ in their job title, or if it’s a smaller organisation, just ‘human resources.’
4. Start with what you know
Beginning the conversations as Kinga did with someone she already knew can help get the ball rolling and make things seem less daunting. Then you can ask… who else do they think you should talk to? Grow the conversation from introductions rather than having to make ‘cold’ contacts.
5. Make things manageable
Kinga found it too overwhelming to aim herself at an entire work sector. Try to break it down to a manageable set of targets, e.g. a ‘hitlist’ of companies that work on problems that you’re interested in solving, or organisations that work towards a mission that is important to you. In doing this, you can also leverage your background and your expertise to your advantage. For example, although she wanted to switch from research to data science, Kinga chose to focus on environmental companies. These organisations not only matched her values, but also appreciated her academic background in ecology and ecosystems. A connection between your academic background and the organisation’s focus could increase the likelihood that you will resonate with them in conversations/ interviews.
6. And finally… polish that CV!
Something that Kinga found worked well for her was quantifying her experience into achievements that an employer would understand and value. So on her CV, instead of finding very technical descriptions of her research, you get ‘punchy’ bullet points like:
– Designed and built interactive time-series visualizations of 1M+ wetland water level measurements, which identified key performance indicators of wetland health and supported smarter decision making about restoration practices
So, focus on tangible examples of the difference that your work has made, or could make… then employers can see how you can help them to make a difference too.
Find out more about Kinga on her website or by connecting on LinkedIn.