Well, what a crazy 10 months it has been for all of us. At Logikk, we’ve seen dramatic shifts in the employment market due to the knock-on effects of the Covid pandemic. Not just in new ways of working and new processes for hiring but sadly in the extensive use of the furlough scheme and large-scale redundancies.
If you have found yourself struggling to find work at the minute, in this article I will be shedding some light and advice on how to develop a solid job searching strategy and hopefully give you an initial edge over other candidates. Whilst this is centred around Data Science, I’m hoping you can adopt and/or adapt this strategy to find a job in other tech-related areas.
1) Optimise your online presence
When looking for a job, there is the obvious task of uploading your CV to various job boards and applying directly to companies via their career pages. However, while this is important, the first thing you should be doing is making yourself searchable. It’s hard enough searching for the right job to apply to, don’t make it hard for recruiters to find you as well.
Make yourself searchable
Firstly, if you haven’t already, get yourself on LinkedIn. LinkedIn is the largest professional social network with almost a billion monthly users and 30 million companies using the platform – it’s the one place you can guarantee to get noticed if you are looking for work (provided you follow the next steps, of course )
While we will create targeted searches outside of LinkedIn (i.e. identifying users pushing repos on GitHub in a particular language or with the most academic citations in a particular research field on Google Scholar), it’s much harder to know if you’re really relevant for a role unless you also have a detailed profile on LinkedIn. Make this your first priority.
Assuming you have an account set up, if you are looking for a new job then make sure you have activated the required preferences on LinkedIn – set yourself as “open to finding a new jobs” and that you are able to “receive messages, or InMails as LinkedIn calls them”. It’s no secret that most recruiters will typically prioritise contacting people who appear to be looking for work.
OK, now the basics are covered, the next key thing is to think about is standing out from the crowd. With so many profiles on LinkedIn, building one that is personal and unique to you is really important.
Who is going to be searching for you?
The top answer here is both agency recruiters and internal talent teams, along with hiring managers who are tasked with their own recruitment.
There are so many nuances within Data related roles, in turn creating an abundance of different job opportunities that require differing skills and experience – recruiters will be searching for profiles using targeted searches and boolean search strings to pinpoint the perfect potential candidates. This means it’s super important to give a detailed account of your experience, responsibilities, and projects – to ensure that you can be found in the first place.
Details are important
It’s also really important that you’re not just listing your latest job title at company X and littering your profile with loads of buzzwords and a bullet list of all of the techniques and technologies that you’ve been using. Yes, people will be able to find you that way, but you need to tell people what you’ve actually been responsible for and the impact this has had.
Having a clear breakdown of your responsibilities and achievements provides the reader with a better understanding of your skillset and specialisms.
I’d also recommend writing something about yourself in the section provided. You are, of course, human and this is an opportunity to get your personality across and talk about your passions and interests – you never know what you’ll have in common with the reader or even the hiring manager. It’s important to remember to keep this friendly and professional, but also somewhat aligned to the type of position you are trying to get hired for.
Provide useful links
You can further enhance your profile by including links to any other URLs – including personal websites and code repositories where you have been contributing to opensource or your own personal projects – by demonstrating that your working and learning in your own time, this will further display your enthusiasm in the work that you do.
Recommendations build credibility & trust
Having recommendations from past employers or colleagues is also a great way of displaying additional credibility. It can be a great way to stay in touch and show your appreciation to past colleagues by asking for and exchanging reviews of each other’s work. Never be afraid to ask, if you don’t ask you don’t get and you will be surprised how many people are willing to help you and the positive things they have to say about you.
2) Build your network
You should always be thinking about how to actively build and nurture your own professional network. This is still possible in a Covid world.
One of the most important things to keep in mind here is that it’s all about give and take. Make sure it’s not all about you and think about how you can give back and add value to other people. What could you share? Who could you introduce? As the saying goes, what goes around comes around.
Maybe start with looking at your activity and engagement on LinkedIn and other social platforms and forums like Quora, Reddit and KDNuggets. The more active you are, the more visible you will be, giving you more opportunities to grow your network. Think about following and commenting on posts by key influencers in your space, to gain further exposure.
Connect with peers and engage with their content and posts too. If you relate to what they are saying, or have a solution to a problem they are trying to solve, then let them know. If you’re brave enough, even think about posting your own original content through posts or articles, this can really set you apart but it might mean stepping out of your comfort zone or be a skill you need to develop.
Don’t get disheartened if you don’t see results straight away. Persistence and consistency is also important, in order to gain traction – there is no point doing it for a week and then stopping.
The larger your network, the more opportunities you’ll have to engage and build new relationships, but most importantly – collaborate with others. It will only help create more chances of hearing about interesting projects and gaining further experience, or better still – new job opportunities.
If you lack experience and are entering the market as a fresh grad, don’t be too proud of gaining experience by working or collaborating on projects for free – at least you’ll be working on a real problem and you never know where this could lead.
Another avenue to explore if you are just entering the Data Science / Machine Learning market and/or if you are transitioning from academia to industry are the Bootcamp offerings. Companies such as S2DS, WeCloudData and Cambridge Spark offer you the chance to learn whilst gaining experience working on real-world problems for organisations (there is also the opportunity to get hired in some capacity off the back of it).
One positive thing about this pandemic is that most, if not all, events are now online – meaning you can attend from the comfort of your own home. MeetUps are great – but you should be also looking at conferences – which, because they are online, are hugely discounted.
Some notable ones coming up this year include:
CVPR – 19th – 25th June
ICML – 18 – 24th July
NeurIPS – 27th Nov – 5th Dec
Re:Work – conference dates throughout the year
All of these will enable you to keep up to date with the latest advancements in the field and offer fantastic networking opportunities. There are also always companies looking to hire at these events.
Hackathons and other competitions (such as Kaggle) are also a great way to collaborate and meet new people – as well as honing your skills or showing off your abilities. Some companies use these for hiring purposes – so get involved if you are able.
3) Be realistic and targeted
OK, so desperation is never a good thing – being realistic and targeted in your approach is really important.
Now is probably not the best time to be looking at a career change and there is no point applying to jobs that you are not qualified for.
It’s also counterproductive to be applying for everything. That will just damage your credibility and you’ll more than likely end up getting ignored. It’s kind of the same thing as a recruiter continuously bombarding you with irrelevant job opportunities. It’s just not cool.
As mentioned previously, organisations are typically looking for a specific set of skills and experience. There are so many nuances in this field and in job roles, so just because you call yourself a Research Scientist, doesn’t mean that you are right for every single research scientist position. E.g. if your background is solely in Computer Vision, it’s pretty unlikely that you are going to land an NLP position at the minute.
If you don’t already, it’s worth learning some basic Boolean to pinpoint specific jobs. Stick to what you know and only apply for positions that you really want and are actually qualified for – you’ll get a much better response rate.
Salary expectations are also something to think about. Given the obvious economic factors (and the added maturity of the Data Science industry), what businesses are willing to pay now is not where we were 2 years ago. Just because you have a PhD and Facebook/Google were paying people 100K straight out of Uni, doesn’t mean that is what you will end up getting.
Don’t always compare yourself to friends or colleagues. We have plenty of conversations with people expecting their “market worth” to be much higher that it is, because someone from their course managed to secure an offer from Google in San Fran paying the world. The reality is that, by doing this, you’ll be pricing yourself out of potentially career defining opportunities because you are chasing money… The money will come the better you are at your craft and experience you can bring to the table.
The winning strategy in a job-driven market
Before covid struck, anyone with stellar Data Science, Machine Learning, Data Engineering or DevOps skills and experience was hot property. Demand for these skills far outweighed the supply so you could more than likely make minimal effort and job opportunities would land in your lap.
Sadly this is no longer the case, this will change once the market recovers, but at the minute competition is high across the board with a lot of great people on the market who have been furloughed or made redundant, so sticking to a job search strategy is ever more important.
Going back to organisations looking for a particular set of skills and experience, staying niche and relevant is also a great way to stand out from the crowd.
Play to your strengths
Having a good grounding in a broad field is important, but clients of ours are always looking for a specialist of something, rather than a generalist or “jack of all”. The many nuances in machine learning and technology in general, offer a fantastic opportunity to become a specialist in a particular area. i.e. reinforcement learning, computer vision or NLP. There are even subsectors of these such as multi-agent systems, autonomous driving or knowledge graphs if you want to take it one step further.
Getting to know one or a couple of industries in detail is also a good idea. Immerse yourself in them, learn to understand what is driving them. You’ll soon see that most companies in an industry will be trying to tackle the same problems, which means they will also typically be looking for the same set of skills and experience.
Tailor your CV
It goes without saying that your CV needs to be a good reflection of you. Like your LinkedIn profile, make sure it has plenty of detail in there, along with what you achieved and the impact you had. If you are applying for a position that lists a number of requirements, make sure you tailor your CV accordingly. I shouldn’t need to remind anyone not to fabricate anything here, you’ll only get found out. It’s also worth mentioning that (unless you are applying to an academic or purely research opportunity) that your CV should, where possible, focus on highlighting your experience in “real-world”/commercial projects and less centered around your publication history. Publications are definitely worth mentioning, but maybe pick your Top 5 (i.e. most cited) rather than all 50 and ensure you include a link to your Google Scholar profile.
If you are being represented by a recruiter, they should be taking the time to really get to know you, so they can relay just how amazing you are to their client. Most good recruiters will only send a small shortlist to a client (3-5 CV’s max) – so if someone has not taken the time to really dig into your experience, what drives you, what you’re passionate about and motivated by, chances are they are slinging mud at the wall and you are one of many.
If you are applying to a company directly, make sure you personalise everything. If they have the chance to send a cover letter, write one. Whatever you do, please do not copy and paste, as it’s very obvious. Just as obvious as a recruiter who has scatter gunned the whole of LinkedIn without bothering to read anyone’s profile. Someone is much more likely to respond if you take the effort to explain why you want to work there and what you can offer them specifically.
I would say one of the most important things to do right now is following up. If you have applied for a job but have not heard back within a few days, if you truly believe you are a great fit, find the name of the recruiter if you can and give them a call. Let me explain why… pre-pandemic, if we posted an advert, we’d be very lucky to receive 1-3 really relevant applicants (and more often than not, zero!). Typically, more than 90% of the people we place come from referrals/recommendations from our network or proactive headhunting. However, over the last 10 months, it’s not been uncommon for us to receive upwards of 2-300 applicants from direct advertising and (most importantly) a much larger proportion of these have been a great fit for the roles advertised, so it’s always worth following up to ensure you haven’t been overlooked. At the very least you’ll make contact with someone who knows you are looking for work, (hopefully) takes the time to understand what you do, and will keep you in mind for any suitable opportunities moving forwards.
Also, try not to get too discouraged if you’re applying and not getting anywhere quickly. Call us and have a chat. We’d happily give you pointers and tips that are more specific for your situation – ask for feedback,” why didn’t you get the job”, “why weren’t you put forward”, “how could you improve your CV / Interview technique” etc. (but, be polite and humble when doing this please – we’re only human and have feelings too :-))
So, who is hiring?
Of course, the demand is certainly not where it was 12 months ago, but the good news is that there are still industries and businesses out there who are still thriving and hiring new employees.
Firstly, think about how Covid has affected certain industries in a negative way – like any type of travel or transport, supply chain, retail, entertainment, tourism and sports. Also think about knock on effects of drastically reduced revenues which is forcing businesses to cut non-essential costs – so PR, Marketing and Advertising agencies who align to those industries are also likely not having a great time right now.
Industries that are doing well are health, pharma, food and of course, technology. There are of course some anomalies here. I won’t mention names but there are a number of Tech businesses that have also made a fair amount of redundancies. I can’t say for certain, but my guess is that they’ve got their products to a certain level where they perform well, so are taking stock, having a reset and evaluating which direction to go in – whilst keeping costs to a minimum and not investing in innovation in the short-term.
Of course the likes of Apple, Google, Facebook and Amazon are not slowing down, but a lot of larger non-tech companies are focussed on cutting costs. They have either put recruitment on hold altogether, or are not using external agencies in order to reduce spending. We are starting to see some light at the end of the tunnel, but it’s going to be a slow process and could go back to getting worse before it gets better.
A lot of well-funded start-ups are still looking to hire. Many of them are seeing this as a great opportunity to snap up some great talent that has been cast aside by some of their larger competitors.
The fortunate thing is that niche skills are the ones still being recruited for. So, going back to my point about finding your niche, if you don’t already have one – now is the time to start.
It’s important to remember, with so many businesses committing to a flexible and remote working policy, as long as you’re comfortable working slightly different hours if you need to, then there is no reason why you could also be considering jobs outside of your current country of residence.
International experience looks fantastic on a CV, because everyone’s approach is slightly different. You’ll gain really valuable experience to different cultures and new ways of working.
So, think globally.
Other useful reading:
This article was aimed at offering some advice on a job searching strategy. We haven’t even touched on some other important factors, including preparing for interviews and learning the right skills. You may also want to check out a few of the previous articles on our website.
One from myself on “how to be a great Data Scientist”
… and a 2 more from a couple of awesome guest authors, who are well respected in the industry.
Andrew Jones, Founder of Analytics Link and Data Science Infinity (who I’d also really recommend checking out!! Not only does he offer DS training, but he has some great resources available around succeeding in the world of Data Science – https://www.analytics-link.com/) on “Data Science Interviews at Amazon”
Ben Dias, Director of Data Science at EasyJet on “What hiring managers want to see in Data Scientist CV’s”
Thanks, and how can Logikk help?
To give you a little background about me and Logikk. I’ve been working in the recruitment sector for over 16 years. I started my career placing software engineers who were largely working on projects related to oil reservoir simulation, F1 race simulation, distributed systems, and complex web platforms.
For the past 7 years, I have been immersed in the world of data. I feel very lucky that I get to talk to incredibly bright people on a daily basis – many of whom are making a positive contribution to the world we live in today. Such as tackling climate change, early disease identification, and personalised drug development.
We started Logikk in 2014 when Dan and I decided to solely focus on recruiting in the rapidly advancing data space.
Our core areas include:
- Machine Learning Research and Engineering – anything Computer Vision, NLP, Reinforcement Learning & Robotics etc.
- Data Engineering and Architecture – think build of data platforms, scaling of data pipelines, and deployment of models.
- Data Science and Analytics – more traditional statistical analysis and insights.
- Reporting and Visualisation – which kinda speaks for itself.
We’ve seen the market evolve dramatically since our inception – from many organisations hiring data scientists just because everyone else was doing it and without really thinking about what problems they wanted to solve. To a world filled with ground-breaking companies tackling some super complex and challenging problems.
We were founded in London (UK), but now have additional entities set up in both Canada and Germany.
Our client base includes well-funded tech start-ups and scale-ups to large household names. We typically work in very close partnership and act more like an extension of their brand, rather than an external outsider. Our business has been built off of the back of strong relationships, which is a testament to our capability to deliver in this ultra-competitive space.
We realised early on that standing out from the generic recruitment crowd is an absolute must – especially when it comes to engaging with data professionals. There is so much noise in the market and traditional recruitment methods just don’t cut it.
Because of this we have been immersing ourselves in the data community by attending and sponsoring plenty of industry conferences over the years – as well as putting on our own MeetUps and hiring Hackathons.
Thanks so much for taking the time to read this, I hope that this is useful information to you. Please feel free to reach out and ask me any questions. If you would like to set up a call with me or any of my colleagues please do reach out, my email is [email protected] … we’d love to hear from you!
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