SDS 108: Working Remotely

Welcome back everybody, to the SuperDataScience podcast. Very excited to have you on board. I’ve got an interesting episode. I was actually inspired to record this Five Minute Friday by the conversation I had with Gabor in the previous episode, the episode that went out two days ago, where Gabor talks about his story and how he’s been progressing throughout his career. Even though he doesn’t explicitly mention on the podcast how he’s getting to his dreams, that this is like the way, with the progression of his dream, for me I can see how he’s moving towards his dreams and goals of being completely in control of his life and doing what he wants and enjoying the work he’s doing, and delivering amazing results, and being able to enjoy his life on his own terms. One of the things that he’s doing currently is, in his new role which he just started a few months ago, he is working remotely. He is working for a company in the US even though he is located, himself, in Budapest, Hungary.

What I wanted to point out here is that a lot of the time, we underestimate, especially in the space of data science, we underestimate what power we have with this information age that we live in. Sometimes people would say that, I want to go live in a certain country but the economy might not be that great there, or it’s very hard to find a job there, but I’m really passionate about their culture or their language, or their food, or have family there, or have friends there. But I just don’t know how it will work out professionally, and plus I have a job right now here where I am and it’s easier to find a job where I am anyway, or in this other place. I think that’s a very limited type of thinking because we have the internet now and you can totally find yourself a job on the internet, an online job or a remote job where you don’t have to be present in the office.

Especially that is the case for data science. Data science is so in demand that companies are forced, even if they are not open to it originally, they might be a bit closed in their philosophy or mentality, they’re still forced to get out there and look for talent. When you think about it, if you’re a business owner, if you limit yourself to the people who are locally present in your location, then you’re limiting the talent pool that you have access to, and why would you do that to yourself or to your company? That’s why more and more companies are getting on board with hiring talent from all over the world. You could be somewhere in Africa and working for a company in Canada or in the US, and as long as you deliver the result, I don’t see why there should be any roadblocks. Definitely, it’s up to you to change your perception of this and your mentality and be able to do that.

One of the websites that I recommend to everybody to get started with this, one of my favourite websites and is actually the biggest freelance marketplace in the world, is called Upwork. Upwork came to be when two companies merged, and these two companies were Elance and Odesk, you may have heard of them, very big companies. So now you’ve got Upowork which is at www.upwork.com so U-P-W-O-R-K .com and all you have to do is go online, create a profile and off you go, you can bid for jobs. As an employer you can create jobs, we post some jobs with SuperDataSCience ourselves there to get some help, but you can create jobs and you can bid for jobs. And this is of course not just limited to data science jobs, there’s copywriting, there’s creative work, there’s legal, anything. You can build a whole team of people on Upwork, a whole remote team.

But as a data scientist, it’s very, very, lucrative. Like, I just went on Upwork just now and I typed in data scientist and the salary ranges or the remuneration ranges per hour, the first ones, I’m just going to read them out from top to bottom what I can see. $45 an hour, this is a person based in Belgium. $100 an hour, based in the US, $45 based in the US, $80 based in the US, $30 based in Argentina, $68 an hour based in the US, $45 an hour based in Croatia, $70 an hour based in Australia, $150 an hour based in the US, $65 an hour based in the US, and there’s like a few pages, like $75 from the UK, $125 an hour from France, $220 an hour from the US.

And what I like about Upwork is that you can see job success rates, for instance this person with $220 an hour, he’s got a 98% job success rate, you can see also how much people have earned, some people have earned $10,000, over $40,000 and so on. Basically, by doing jobs on Upwork, you can build yourself a portfolio of data science roles and build up this expertise. There’s somebody who calls himself an algorithm scientist, I just found them, who’s charged $120 an hour and they have earned $700,000 on Upwork. How crazy is that? And usually amounts like that are earned by agencies but this is a person, and he has a 100% job success rate. Very, very interesting.

It’s important of course to keep your job success rate up, so more people will be interested in your profile, but yeah, you can build yourself a profile in the area of data science that you love. What I also like about it is that you don’t have to make it your full-time job. Even if you already have a full-time job and then there’s some other area of data science that you’re interested in or even your area of data science, you’re interested in and you want to grow your expertise, you can do this on the side as a hobby, earn additional income. As you can see, the numbers are not low, I didn’t even read one, not even one person charges less than $30 an hour as a data scientist, and then you know the average is like $50 an hour. You can earn an additional income, develop your expertise in that area that you’re interested in, help other companies progress.

And the best part is even if you’re not interested in transitioning to full-time remote work, becoming a full-time freelancer … We had the conference, DSGO conference the weekend before last, and during the panel, by the way, you may have listened to the panel, you can listen to it, it’s on the podcast as well, it’s in the previous week podcast. What we discussed, one of the things that I like that Ben Taylor mentioned was that as an employer, he would totally take into consideration and into account freelance work experience. Especially of a platform like Upwork where everything is verifiable, once you’re going for an interview, or you’re looking for a job promotion or anything, you can send a link to your profile on Upwork and say, okay look, I’ve done 100 hours of work on Upwork, I’ve done these five projects, these are the reviews I got, this is what I’ve worked on. It’s all very transparent and is easy to see and employers will and should consider that when looking at your experience. So, all of a sudden you don’t just have the experience that you have at your normal work, you have this additional experience which is even, I think, more valuable because it’s not something that you have to do just to get the pay check, it’s something you’re doing out of passion, you’re doing on the side, you’re doing for fun, for learning, and it stands as a very strong testament to your abilities and also, more importantly, to your enthusiasm about the subject. So, it’s always a good idea.

Especially for those of you who are still students or still looking for your first job in data science, this could be a great way to get started and get started on the right foot because if you do a couple of projects on Upwork and for instance your average, you started charging out $30 an hour, then 50 then 70 then 100, then 150 and then your average charged out rate is like $100 per hour, then you can use that and say, look, I’m charge $100 an hour, that’s what I want to get paid for my full-time work. Well, not exactly that because you know, full-time work you have more job security and you have more hours and you have more guaranteed work. But you can use that as an estimate for how much you’re worth, for how much value you can bring to the company and how much people out there are willing to pay for your work, so why shouldn’t the company pay you somewhere around that same amount? And that was a very interesting comment from Ben Taylor during our panel discussion there.

In general, there are so many pros and benefits to creating a profile on one of these platforms. There’s many platforms for freelance work, Upwork is just one of the biggest ones and if you don’t have any specific preferences, I would highly recommend starting out there. Of course, there’s going to be fees involved, they take transaction fees from you for the administration costs of the platform and so on. But as building your own agenda, and as a profile, and having a profile online and this experience and additional source of income, I think it’s a great solution. As you can see, in many scenarios, it’s a good idea to at least try out this remote work, that’s just the world we live in.

And you never know, maybe you’ll get so into it that eventually you’ll just decide to transition to full-time freelance work and you’ll be able to work from wherever. If you’re charging out like $100 an hour, then you might only need to work three days a week and for the remaining four days you can be travelling, you can be living in Italy, or if you’re from Italy, you can be living in Argentina, wherever, enjoying local cuisine. And also you can go to a country where costs are less and rent is cheaper or food is cheaper, everything’s cheaper, just basically you can build a life of your own making for yourself. It’s just a matter of trying and putting in some effort into it, and I’m sure the fact that you’re listening to this podcast already means that you’re passionate about building a successful career in data science. This is just one of those stepping stones and I highly recommend checking it out.

There you go, that’s my two cents on remote work, I definitely encourage you to check out www.upwork.com and I can’t wait to hear about your success stories. I look forward to seeing you back here next time. Until then, happy analysing.