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Why Freelance Data Science Is Inevitable

by YOSS Community Writer, on July 8, 2019 at 1:15 PM

Top Tier Companies Are Hiring Remote Data Scientists 

Just a few years ago, the idea of working from home or other offsite locations seemed impractical for many industries. Today, not so much. In 2017, Nasdaq predicted freelancers would make up more than 43% of the U.S. workforce by the year 2020.  

freelance data science professional


As the demand for freelance workers has risen, so has the demand for IT experts and data scientists. However, companies have historically been more reluctant to outsource work involving fundamental systems and data analysis. Only in recent years have we seen postings for remote, flexible, and agile contract data scientists to work offsite and on a freelance basis.
  

Now, you can find hundreds of offers for remote data scientist positions on most job recruitment boards. For most companies, data science is one of the biggest, most common, and most important of their skills gaps. If the surge in data scientist job postings is any indication, these companies have recognized the value in filling those gaps with freelance data experts. 

If you are a data scientist yourself, learn more about the data science career path, to see if you are on the right track to succeed! 
 

Why the Sudden Embrace of Freelancers? 

It's only natural that companies are changing their views on freelance work. For the ones that took the risk of hiring freelancers early, the positive impacts were obvious. Worker productivity shot up, overhead costs dropped, and companies suddenly had the ability to access high-level talent of any kind on an as-needed basis. 

A report by Gallup shows that between 2012 and 2016, the number of people who worked remotely at least four days a week rose from 24% to 31%. The study also notes that working offsite made employees much more engaged in their jobs than their office-bound co-workers. 

That higher engagement isn’t an isolated incident, either. In a study lasting nearly two years, Stanford professor Nicholas Bloom discovered an astounding and consistent productivity boost among telecommuters. In his study, home-based employees worked about 9% longer and were 13% more productive than office workers. They were happier, took shorter breaks, had fewer sick days, took less time off, and were half as likely to quit. 

These remote and freelance workers have valuable skills that they could monetize, and now, they have greater freedom to choose the projects that interest them most. Fortunately, companies have realized the need to adapt to this shift in work preferences. They rely on more agile remote teams to complete projects, meet deadlines, and even take the lead on certain initiatives.  

But, What About Data Scientists?  

It’s one thing to outsource some engineering or other tasks to freelancers, but data science is in a class by itself. Data-driven discovery means uncovering hidden patterns and correlations to help companies find out what works, when, and under what conditions. With that data, they can improve programs, allocate resources, and make decisions more effectively.  

In other words, data science insights form the nuts and bolts of a company’s decision-making process; it's the rudder that steers that entire ship. Look at Kickstarter, for instance. The data pulled from its nearly 15 million users helps the crowdfunding platform create and deliver important insights, such as what factors most often contribute to projects getting more backing.

For companies, those kinds of insights are the lifeblood of their success. It’s how they know what messaging platforms generate the most leads, which factors inform consumers’ purchasing decisions, and more. Naturally, they’ve been slower to parse out data science responsibilities to third-party experts, who would need access to that powerful data.  

The importance of solid data science insights and the skill-sets required to produce them are changing companies’ minds about how they acquire data science talent. While companies grow desperate for the right expertise, freelancers are polishing their skills, with as many as 61% of them specializing in at least two or three different talents. 

The high demand for data science talent makes it difficult for companies to find the skilled data scientists they need. When they do, it’s hard to match the freedom, flexibility, and growth that freelancing offers. Today’s evolved freelance platforms make it easy for data scientists to choose the projects that interest them most and for companies to find freelancers to tackle even their toughest assignments. 

Bringing Data Science into the Freelancing Fold 

By 2020, job openings for data science will reach about 2.72 million, according to an IBM study. The position is crucial for companies to turn massive amounts of data into actionable strategies for improving product design, customer relationships, and more.  

Data science and its related skills are no longer buzzwords — they’re essential business tools. So essential, in fact, that the demand for data scientists has risen year over year, with a dramatic 344% increase since 2015. Today, businesses are adopting new management strategies to meet the flexibility of data scientists who choose to work as freelancers. 

Everyone from small startups to well-established Fortune 500 companies are willing to take a more progressive approach to hiring data scientists. Instead of trying to recruit full-time hires, they’re hiring them strategically to complete projects, provide knowledge, build platforms, lead data projects, and advise decision makers. 

For some companies, though, the risk of granting access to trade secrets can be a strong deterrent. They might not realize they can entrust sensitive information to data experts in part or full, and protect it with non-disclosure agreements (NDAs) and intellectual property (IP) contracts.  

Implementing data security protocols into the system also helps keep information secure. Give data experts swaths of information instead of the entire warehouse. Require check-ins with digital signatures to keep track of data access. Use collaborative technology to gain real-time insight into a project’s progress and more successfully manage deliverables.  

Insights From Freelance or Remote Data Scientist Postings 

The dramatic increase in job postings for freelance, virtual, or remote data scientists shows that the benefits of harnessing this vital expertise far outweigh the concerns companies have about outsourcing their data science. However, it isn’t just the vast number of postings that prove freelance data science is inevitable. Consider these facts, as well: 

  • Companies are offering remote data scientists better benefits. 

Whereas companies used to stigmatize the idea of freelance workers, today, they’re treated with just as much respect as full-time employees. Offers include competitive benefits packages and positions that range from contract-to-hire, full time with full benefits (such as 401(k), medical, and PTO), and benefits eligibility without being full time. Biomedical tech company SemanticBits recently posted an opening for a remote data scientist position that included paid time off, health benefits, 401(k) matching, and flexible work hours, for example.   

  • Data science job postings include more flexible work options.  

For more remote positions, companies are offering different options to give their data scientists even more freedom. Deloitte, for example, gives the opportunity to work remotely after demonstrating satisfactory performance. United Health Group and Oracle have posted opportunities for fully remote data scientists. And Dell and USAA have positions available for either remote or on-site workers. Some companies, like Aetna, Glassdoor, and American Express, even offer telecommuter options for multiple roles across their organizations. 

  • Even data science leadership positions can be remote. 

Continuing the expansion of freelance work to data science is a big step, but some companies are taking it a step further by also offering senior, director, principal, and leading data scientist positions. General Mills, Oracle, and FireEye Inc. recently posted openings for senior data scientists;, United Health Group offered a principal data scientist position,; and The Hartford was looking for a director of data science. All these opportunities included remote options.

Data science leadership opportunities allow remote data scientists to direct employees, make decisions, take up mentorship positions, and directly advise top-level executives. Several of these posts ask candidates to play critical roles in leadership and strategy teams, define functional and research roadmaps for the business, and help the data science team grow.  

  • Trust in freelance data scientists is growing. 

More companies that deal with sensitive data are entrusting remote data scientists with critical responsibilities. Industries including fintech, health insurance, medical technology, cybersecurity, and even governments are offering positions to freelancers that include handling high-risk and sensitive data. 

Cybersecurity company FireEye, Inc., recently posted a remote senior data scientist opening that involves overseeing the advancement of machine learning in the threat detection arena. And FinLocker, a financial data and analytics business, sought a remote or contract data scientist to help create a program that essentially acts as a robo-advisor for clients, analyzing their assets and other financial data. Both of these companies must trust their remote data scientists to complete their work in a professional and careful manner, considering that the data at hand is critical to clients' lives and businesses. 

  • Organizations of all sizes are embracing remotedata science work. 

Companies at the forefront of innovative tech, such as AI and machine learning, are also at the forefront of recruiting freelance data scientists. They are not alone. Top-tier companies from the Fortune 100 and Fortune 500, such as Humana and Target, as well as multinational and industry-spanning conglomerates such as Capax Global LLC all have multiple open positions for remote data scientists. Companies including software startup Tesorio, engineering and consulting firm CMY Solutions, and the American Heart Association are jumping on the remote data science train, offering these positions as small to mid-size businesses. 

  • Data science is important across industries. 

Data drives everything from industry to government, and the importance of analyzing and understanding it is recognized worldwide. Freelance data scientists are now integral parts of policy research, business development, agriculture, infrastructure, power engineering, civil engineering, transportation, and more.  

Some companies might still have lingering concerns about whether or not they should outsource the task of managing their data to one or more freelancers. Yet, those concerns are continuously calmed by the growing success companies and data scientists are experiencing with a more flexible workforce model. 

The importance of data science is undeniable, and so is the pressing concern about the shortage of available full-time experts that companies can recruit. Many of the most successful companies have embraced the idea of hiring remote data scientists in order to fill critical skills gaps and increase business value. With the right freelance platform on your side, finding the trusted talent and skill set you need is easy. 

To learn more about how YOSS helps connect top freelance data scientists to companies in need, connect with a YOSS team member today.

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