Like all things on this blog, we’re really here to emphasise social mobility and to help you pave the way towards your next fulfilling and satisfying career. Almost a quarter of the way through the 21st century it would be ignorant and shameful to not even touch upon the tech industry or the tech space. As we move towards an increasingly digital age, with large social media platforms, facial recognition, blockchain, crypto currency, web3, and more, there is a growing amount of demand for employees to have some knowledge or at least some skills that overlap with the tech space. Fortunately, the nature of tech is rapidly evolving, fast paced, relatively democratised (when you think about access to education, it’s notably easier to learn how to code online for example), enabling a whole host of people to make the jump.
In this post we’re going to provide a starting point, how to make the jump, and how to pivot from academia (no matter what your discipline is) and into the world of tech. This isn’t the only guide you should rely on, but it’s here to get the ball rolling and we’ll leave you with some things to consider and how best to proceed. Like every career decision you make, we always want to stress and emphasise the importance of your life values and picking a career that aligns with them – not one that sounds cool and hipster.
Having said that, the tech world may offer some of the more ‘attractive’ opportunities. Most organisations in this space typically come with a good salary, reasonable work-life balance (obviously this varies organisation to organisation), a whole host of perks and benefits, a high probability of remote working, the opportunity to develop and continue learning, and of course a good chance of longevity – it’s unlikely the tech or digital era is going to end so getting into this industry sooner may set you up for success over the long haul.
To start with, in the world of tech, the easiest and more commonly understood roles is the world of data analysis. Here, you’ll be doing reporting or number crunching with a range of software’s and tools. Data roles can be diverse and rich, providing a lot of variability between them. Some organisations will be set up with data at the heart of their decision making, some won’t even know what data is – but will be keen to move in a data-driven direction. In turn, what you’re doing when it comes to analysis will vary from company to company. A nice starting point, or at least transitioning into the data and tech space, can be to focus more on acquiring the basic/fundamental ‘hard’ skills.
Starting with certain software’s like Excel, SQL, and a visualisation tool (such as Power BI, Tableau or Looker) are a great way to demonstrate your knowledge of data and data analysis. By combining these hard skills with your research knowledge from your PhD alongside the other transferable skills, there’s no reason why this path is outside of your grasp. Overtime, you can begin to transition into other programming/data analysis languages, such as Python or R. If you’ve come from a STEM or possibly even a non-STEM background, having some familiarity with tools like SPSS or STATA are likely to make the transition easier. However, it’s not the be all and end all – a core function is that you take some numbers and produce some reports/insights. Being able to think critically, communicate effectively, and solve problems is something extremely familiar to all PhDs.
Another strand that’s commonly centred around the tech world is UX, or user experience. UX is a world where you’re essentially collecting real-world data (and here we mean the loosest forms of data) to provide recommendations and guidance to the way something is designed and made to look like. For example, you might be doing UX research for a company looking to build a new website. In turn, you might do some questionnaires, engage with the users, run some focus groups, design some surveys, or whatever else to find out what the consumer needs from the website.
You might seek feedback on what does or doesn’t work for the website and so on and so forth. Once you’ve got your data/feedback, you’ll then present these insights to the team responsible for building the website so they’re able to understand what it is they need to change and why. Again, these skills align with the PhD journey incredibly well, being able to run focus groups, speak at conferences, and managing projects is the bread and butter of PhD life. As long as you’re able to communicate how well your PhD aligns with UX roles, this could be your ticket into tech.
The final tech role that’s great for entering post-PhD is what we can refer to as ‘product roles’. Just like the ones mentioned above, these are ill defined, with a lot of variability. But in essence, a product manager is going to be quite similar to a UX role – whereby you’re on the hunt for recommendations and consumer feedback. Another way to think about it is someone who acts as the ‘bridge’ between those who make the ‘product’ and those who ‘use’ or rely on the product.
This could be the way websites are designed like in our previous example, but also how reports are built, certain data facing products like dashboards look, and possibly even the structure of questionnaires or other products that data analysts, engineers, or marketers might rely on. Product management, or product owners will vary from company to company, and it’s not unheard of for different job titles to exist for these roles. The great thing about product roles, and possibly UX roles, is that you don’t necessarily need ‘hard’ tech skills. Your key responsibilities are again, communication, research, providing recommendations, and being able to organise larger projects and engage in some strategic thinking.
But how do I start? Well, firstly it’s to mould your CV, LinkedIn profile and other personal branding content to align with these professions. Secondly, it’s to begin building your network with people in this space, reach out to them on LinkedIn, go to a couple of interviews, reach out to people you know. The objective is to really understand and get a sense of what these roles do – that way, you’ll also learn how to talk to people in this space in the correct way. Finally, it’s putting in the work to make sure you learn anything necessary for the respective role. Whether that be in the form of tech skills, project management, or anything else.
This is not a comprehensive list, if anything it’s a nice gentle introduction to some possible opportunities out there, or at least where to start looking if wanting to end up in tech is the long-term plan. You don’t necessarily have to stay in the first role you end up in – sometimes it’s just about getting into the correct industry first, in any capacity, and then you can begin to fine tune a little further as you learn new things in your new role. Either way, it’s hard work, but you’re a PhD, and there’s nothing out there you can’t do.
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