This most straightforward way to tackle this problem is by hiring a data scientist for the organization, but this isn’t always the best option. Data scientists are in high demand, and at the same time they are in short supply. Data science is a relatively new field, and universities are only just starting their own programs to train up a new generation of big data experts. That means that the number of qualified data scientists is low while companies all over the world are out trying to hire the best. The result, as can be assumed, is that good data scientists command high salaries. Bringing a full time data scientist on at a small business with a low budget simply isn’t a reasonable choice. Perhaps some time in the future, as a small business expands, they’ll be able to afford having a data scientist on staff, but for now, they’ll have to look at the freelance pool.
One of the major benefits gained from going the freelance route is flexibility. Instead of hiring a full time data scientist to oversee all big data projects within an organization, the company instead hires on a per project basis. This is especially important for smaller businesses, since the time between big data projects at that level can often be lengthy. Passing over the full time option means a business wouldn’t have to worry about paying a big data expert when they have nothing for them to do. Hiring based on the project means a smarter use of limited resources. This added flexibility also leads to choosing data experts based off of their individual talents. For example, if a big data project requires hiring a data scientist with expertise in sales, the small business can do so. Their fees aren’t based off of a salary but rather on the milestones reached in the project. And once the project is completed, there’s no concern over keeping a data scientist whose expertise is no longer needed.
The specificity regarding who to hire is also a big benefit received from pursuing freelance big data experts. Hiring is done on very specific needs, and since those needs can change over time (quite dramatically in some cases), it’s important for many smaller organizations to have only the experts they need at certain points. Due to this dynamic landscape, many small businesses choose to try to perform all analytics in-house with apps and tools like Hadoop or Apache Spark. But many of the available tools have a wide range of functions, and without the right big data expert at the helm, the true potential of that tool is unlikely to be reached.
Another area where hiring a freelance data scientist could prove beneficial is in the hiring process itself. For small businesses, HR departments already have plenty of responsibilities and pressures to go along with limited time. Finding any way to ease the hiring burden would be welcomed. Freelance employees are much easier to hire, and with the rise of virtual marketplaces where big data experts can promote their skills, hiring one makes even less work for HR to deal with.
From an easier hiring process to greater flexibility, going with freelance big data experts provides an excellent return for companies, especially small businesses. With the right data scientist on hand, organizations will be able to use big data to expand their businesses. With more growth, perhaps hiring a full time data scientist for the company will become a possibility. In the meantime, freelance hirings are a safer and more affordable bet.