The data scientist role has quickly gained a reputation for being one of the most in-demand jobs, and the need for those professionals shows no signs of waning. The immense demand for these professionals has given rise to a new role: the freelance data scientist.
Data scientists assist companies in numerous ways, such as determining which products sell best or which demographic groups respond to certain marketing campaigns the most. The immense demand for these professionals has given rise to a new role: the freelance data scientist.
Data scientists can also help reduce instances of fraud and other issues that may negatively affect a company’s bottom line. If you’re eager to start tapping into the benefits of having at least one data scientist on your team but have some hesitations, consider hiring a freelance data scientist first. Here are five reasons why doing that could work out well for you.
1. It’s quicker
Human resources professionals often talk about the time-to-fill when they discuss how to meet their hiring needs. It’s a metric associated with the length of time between the time when a company has a candidate for a role and when that person accepts the job offer. Research shows that it often takes at least a month for companies to source new hires according to that metric.
Plus, you can’t forget that the conventional hiring process typically includes an onboarding aspect, and it takes time to put the person through an orientation, set up their company email access and logins for other corporate tools and go through human resources paperwork to understand about paid time off, retirement plans and sick days.
If you decide to take the freelance route for hiring a data scientist instead, it’s possible to cut out many of those things. Consider that most freelancers don’t receive — or expect — company benefits, so there are fewer specifics to go through with them.
Rather than launching an onboarding process that could otherwise take weeks, you could send freelancers a company document that goes through what they need to know concerning things like tracking their time or staying in touch with on-site employees. Then, they can refer to that information whenever necessary and should ideally have a point of contact to use if any issues crop up.
The timeline for finding candidates is potentially much shorter, too. You can start by going to one of the many freelance job boards and either posting information about your ideal freelancer or looking through the profiles of freelancers using the site to see if their skill sets and experience levels match what you need.
2. It’s less expensive
Perhaps you’re in a scenario where you’re fully on board with how data science expertise could help your company, but the decision makers who control the budget are more cautious. In that case, they may not be willing to give you the funds necessary to hire someone as a full or part-time employee, making a freelancer an ideal compromise.
Or, it could be that you’re part of a startup company that embraces the need for data science assistance, but the budget of the business is modest across the board. In cases like these and many others where money is a primary concern, you’ll likely find it’s possible to hire freelancers at lower rates than company employees anticipate. On Kolabtree, for example, freelance data scientists typically charge in the range of $35 to $200 per hour, and the typical rate of a fixed fee project is $2000.
3. Time differences may help with meeting deadlines
Deciding to hire a freelance data scientist could also open the size of the candidate pool. It’s worthwhile to realize that focusing on data scientist freelancers gives you the chance to look for people who live in other countries.
For example, if you hire a freelance data scientist who lives in a part of Europe where the time zone is five hours ahead of where you live in the Eastern United States, that person could start working well before anyone on your side of the world wakes up. That benefit could be especially advantageous if you have clients requiring that their data science projects get completed by hard deadlines.
4. You can assess freelancers before giving them more work
A Forrester Research investigation published in 2017 found that 99% of respondents deemed data science an important discipline to develop. If your company wants to proceed cautiously with such development, the path to doing so might include giving projects to freelance data scientists with the intention of hiring them as non-contract-based contributors if those workers meet expectations. This can become a part of your businesses strategy to help scale your business.
You could either tell the freelancers at the start that there’s a chance of becoming employees if they perform well. But, it may be better not to mention that possibility until it becomes evident that their output and the quality of the work reaches a standard that makes it smart to hire them as employees.
But, consider that some freelancers may not be open to the idea of becoming employees. When FlexJobs polled freelancers to determine why they chose that method of making a living, the results showed that 62% of people did so due to the work schedule flexibility offered. If working for your company in a capacity other than freelancing might compromise that flexibility, some people may not want to do it.
It’s wise to ask something during your freelance screening process such as “Would you be willing to consider taking a full or part-time position with us if an opportunity existed?” Then, people shouldn’t expect that outcome, but at least you know how they feel about it.
5. Reduce burdens on your in-house staff
If your employees feel like they work too hard for too little pay or are unhappy at work for another reason, those people could be prone to burnout. Kronos carried out a study indicating that almost half of human resources polled said that employee burnout was to blame for 20 to 50% of their turnover. One of the positive consequences of hiring a freelance data scientist is that you could make your employees feel less overworked.
Perhaps you already have a data science team, but they consistently mention they feel swamped by the workload. Or, maybe you recently invested in a data analytics tool and asked a person with limited or no data science knowledge to figure out how to use it, and the task isn’t going smoothly so far.
If people feel frustrated for too long, they may be more likely to decide it’s best to look for another job. You may also find that when people get assigned too many tasks and always feel rushed as a result, the overall quality of the work goes down. Hiring a freelance data scientist could ease these issues, helping everyone feel happier, more productive, and able to excel.
Factor freelancers into your data science hiring plans
This list shows there are plenty of practical reasons to think about relying on freelancers to take care of your data science needs. Data science could help your company become more profitable and competitive. Evaluating capable data scientists who work as freelancers could make it easier than you expect to find the necessary talent.