alinnorugo-blog

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The Gig Economy Is Upon Us

I’ve been a scientist/entrepenuer for the most part of my life. For a child that survived bronchitis in Nigeria when he was 2 months old, I can say I'm lucky to be alive. I conducted my first scientific experiment when I was 8 years in primary school, something that rarely occured in Africa in the 90's. Also, during my holidays, I would follow my dad to his office were I learnt the art of selling. My dad traded in building materials while my mom traded in famly care products like diapers and sanitary pads. I went on to college where I studied biochemistry and minored in physiology. When I was in college, in addition to reading science books I also read business books and pondered about starting a business when I graduate. Upon graduation, I still took some courses on Data Science before setting out to manage my mom's business unit. During my time as a business manager, I stroke deals with high-end clients which helped triple the revenue of the company in less than 9 months. However,at the turn of the year, I resigned my position to focus on my career as a Data Scientist.

So why did I choose Toptal? After I graduated with certifications on Data Science from Experfy and Datacamp, I decided to set up a company that specializes in Artificial Intelligence. But who do I sell my services to? To the world! So I thought. In reality, the world is fragmented and clients differ from industry to industry and from geography to geography. And that's where Toptal comes in. After researching on which freelancing best suites Data Scientists, I discovered Toptal they had a compelling story- A freelance site with a completely remote team distributed throughout the world. Another thing that stroke me is it's rigorous application process. As a machine learning expert I would like another expert to review my work so I get feedback and improve on my skillset immediately which doesn't happen in sites like Upwork.

The Gig economy is upon us: The Gig Economy is a labor market characterized by the pervasiveness of contracts or freelance work instead of typical, permanent jobs. With an estimated 50 to 68 million gig workers in the US, it's obvious that there's a new type of 9 to 5. With Freelancer’s Union predicting that 40% of the  U.S workforce to be freelancers by 2020, and 80% of large corporations planning to increase their use of a flexible workforce, the gig economy is only getting started.

Considering that what we Data Scientists, Software Engineers, and Writers do is mostly cognitive, it is much more efficient to work from home. You don't have to drive through the traffic or get exhausted from driving. As a freelancer you simply get up have breakfast and get to work - on your laptop. I will like to be part of the most selective freelance site in the world.

In conclusion, I’ve just began the interview process at TopTal.com (to become a part of the Toptal R Development Group.), and I really like to get in and become one of the freelancers who work there. If you’re a Data Scientist looking for work, I recommend that you do the same.

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Why R Has Become The Programming Choice For Data Scientists

A recent report by Institute of Electrical and Electronics Engineers(IEEE) stated that R programming language - the king of statistical computing languages for analyzing and visualizing big data takes 5th place in “The 2017 Top Ten Programming Languages”,  this is an extraordinary result for a domain-specific language. The other four languages in the top 5 (C, Java, Python and C++) are all general-purpose languages, suitable for just about any programming task. R by contrast is a language specifically for data science, and its high ranking here reflects both the critical importance of data science as a discipline today, and of R as the language of choice for data scientists.

So why has R programming language soared in popularity in recent years? Well, it depends on who you ask. The answer varies, for example IEEE Spectrum ranks languages according to a large number of factors, including search rankings and trends, social media mentions, and job posting while statisticians say its because of it's rich packages.

Here are my top 5 reasons why R has grown in popularity

1) R language is Free

R is an open source programming language-free for anyone to use. R language code can be executed on all platforms Windows, Mac, or Linux. Data geeks can inspect R language code and play with it as much as they want without having to bother about user limits, subscription cost and license management. The programming libraries are free to access, however there are certain commercial libraries that are meant for organizations that often deal with data in the terabyte range.

2) Large ecosystem

R has a rich ecosystem of cutting-edge packages and a large active community. Packages are available at CRAN, BioConductor and Github. You can search through all R packages at Rdocumentation.

3) Lingua franca for  data science

R is developed by statisticians for statisticians. They can communicate ideas and concepts through R code and packages, you don’t necessarily need a computer science background to get started. Furthermore, it is increasingly adopted outside of academia.

4) Visualizations

Visualized data can often be understood more efficiently and effectively than the raw numbers alone. R and visualization are a perfect match. Some must-see visualization packages are ggplot2, ggvis, googleVis and rCharts.

5) Ease Of Use Beyond popularity, another reason that R is an excellent data science programming language is that it is easy to download and install, and intuitive when in use.