Five Tips For Finding A Job In The Data Industry…..

Five tips for finding a job in the Data industry during Covid

It’s fair to say the job market is tough across most industry sectors right now, as a flood of redundancies due to the COVID pandemic has left an uneven balance between the number of people looking for work (many) and the number of jobs available (few). Despite being a significant growth market prior to March 2020, the Data industry is not immune to this phenomenon, and it’s increasingly important to develop a strategy for finding your next role given the wealth of competition. 

With this in mind, I was delighted to take part in a live discussion via Zoom (is there any other way right now?!) recently with 3 experts in the Australian Data Industry, as we sought to answer the question “Is now a good time to shift careers into Data Science?”. It was an enjoyable and thought provoking discussion (you can watch it in full here ), with some excellent points from veterans of the industry on how to make the change into this exciting and fast moving sector, even in the challenging times we face.

However, it got me thinking – surely the lessons we discussed are relevant to experienced job seekers in the industry too? As a specialist recruiter for the Data industry in Australia, I’m experiencing a massive increase in applications for each role I recruit, many from experienced data professionals who would normally be highly sought after in a normal market. When talking to these people, I find many haven’t had to try too hard to look for their next role – often they’ve been headhunted by people like me! – so I thought I’d condense what we discussed in the above podcast and make it relevant for experienced Data Professionals too. My five top tips in the current market would be:

Get yourself noticed

In a competitive job market such as the one we find ourselves in – where employers have multiple options available to them – getting your details in front of the right people is critical. Linkedin is still the number one place for this in Australia, and the good news is most of my clients are spending more time on the platform than they did pre-Covid – so it’s a great place to get noticed. Make sure you have a Linkedin profile that clearly defines your skills and experience, as well as what you are looking for. Think about commenting on industry professional’s posts in a thoughtful and informed way, demonstrating you know the industry they work in. Other useful ways to get noticed outside of Linkedin include joining meet up groups for Data professionals (yes, they do exist!), although be aware that many of these are operating virtually at the moment.

Do your Research and be proactive

Identify companies that you may be interested in working for and industries that may be growing rather than shrinking. Let’s face it, you have a much better chance of securing a role in a sector that’s growing, so why waste your time approaching sectors that are making staff redundant? Once you’ve identified which companies and industries to target, proactively approach them. There are a number of ways to do this, including via Linkedin, direct email, or using a specialist recruiter to do this for you. There is no right or wrong way on this - it’s whatever you feel most comfortable with – but stay clear of directly asking for a job! It’s must better to say that you’re available and currently researching the market. Wording is important, which is why many use a third party to approach companies on their behalf.  

Work on your communication skills

Reviewing your interview technique using the STAR principles (there’s a link to these here if you aren’t familiar with them), can be a great way of getting ahead of the game. You might also want to consider practicing them with family and friends using Zoom or other similar online tools, as many initial interviews will be online in the current climate. Having a good grasp of the technologies’ employers are using to screen and assess candidates, as well as being comfortable with communicating through them, will stand you in good stead. Hiring managers often tell me that the difference between a great candidate is not technical skills its communication skills, even in highly technical disciplines like Data Science or Business Intelligence, so it’s worth bearing this in mind. 

Consider mentoring someone else in the industry

If you have extensive experience in your chosen industry, and more time on your hands than you are used to due to the challenging job market, why not consider sharing your knowledge with someone in the earlier stages of their career? Mentoring is a great way to give back to the industry, will improve your coaching skills (which are often in demand for senior roles) and is also something you can add to your resume or Linkedin profile. Mentoring will also expand your industry network, which is critical when pro-actively searching for your next role. 

Be Persistent and Consistent in your approach 

It might seem obvious that you need to be persistent when searching for a role at the moment; however, combining this with consistency can really pay dividends. For example, set a routine for yourself to contact a specific number of people each day (then stick to it!), and continue to regularly post on Linkedin with industry related content. Sharing relevant articles is a great way to show you are engaged in the market (even if you aren’t currently working in it), and a weekly post will keep your name front of mind with potential employers. 

Hopefully these tips will give some readers a few ideas on how they can improve their chances of securing that next role, even when there are fewer of them about than usual at the moment. As a specialist recruiter for the Data industry, I know I would be impressed if a candidate I was working with was doing most of the above, and I’m pretty sure my clients would feel the same way! I’m always happy to act as a sounding board for experienced job seekers in my chosen market, so feel free to contact me if you feel this may help.

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Is now a good time to shift careers into Data Science? (Podcast)