Data science is an ever growing field that provides countless benefits for businesses. Whether you’re starting a new company or yours is already established, you’d be surprised to learn some of the amazing benefits of hiring a data scientist (DS). If you’ve been thinking about it for a while, you’re in the right place.
When hiring a data scientist, look at which degrees and courses they’ve taken, how long they’ve been a data scientist, and which programs they’re qualified to use. Some data scientists have a broader range of experience with coding and creating algorithms than others. In most situations, such diversified experiences make applicants more suitable for the job and hence the hiring.
Throughout this article, you’ll also learn the following info about hiring a data scientist:
- Why it’s a good idea to hire one for your company
- Pros and cons associated with hiring a DS
- How long it takes, how much it costs, and more
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
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Why You Need a Data Scientist?
Data science has been around for a handful of years, but many companies are now beginning to understand how useful they can be. If you’re reading this post, then there’s a high chance that you’ve been thinking about hiring one for your company. The good news is that it’s much simpler than it seems.
Here’s a list of five reasons that you need to hire a data scientist:
- Data scientists put everything into easy-to-read tables. Instead of having to write everything down and figure out what it all means, you’ll be able to sit back and enjoy the finalized data. Find out how well your plans are working and which details might surprise you to accommodate your customers.
- If needed, you can hire them on short-term contracts to protect your bottom line. Not all companies need Data Scientists as regular employees. There are many businesses that would only need these professionals during the strategy definition phase or for certain special projects. Hence, it is very much possible for you to reap the benefits of the work that a data scientist can do for you without onboarding that talent full time. To do this, you simply need to come up with a project and hire one for a few months to analyze and transfer data.
- They provide details to allow you to adjust your business tactics. HackerEarth points out that data scientists are excellent at optimizing the data of your company. Whether you are trying to convert more sales, sell impulse items, gain more information about your clients, or make things run smoothly, a DS can make drastic changes.
- You don’t have to learn how to code or create algorithms. Coding and conversions can be difficult, especially if you are not well-versed in the tech industry. Most people who are running businesses do not have the spare time to learn coding, algorithms, and how to put everything together. A data scientist will get it all done for you.
- Many of them have knowledge of similar fields in the tech industry. A lot of data scientists know quite a bit about computer science, mathematics, some areas of science, and more. Their classes and courses overlap with similar studies, making their knowledge invaluable for any business.
As you can see, hiring a data scientist is an absolute must for many companies. It doesn’t matter which industry you’re in; you can benefit from hiring one. For those of you who are on the fence about hiring it due to various expenses, proceed to the next section.
How Much Does It Cost to Hire a Data Scientist?
If you have started a budget and you want to know how much you will have to spend on a data scientist, you’ll learn it all here. Fortunately, you’ll be able to hire one as a freelancer. That being said, many companies prefer to hire full-time data scientists. Depending on which route you choose, you’ll have to adjust your budget accordingly.
Freelance Data Scientist
Kolab Tree states that most freelance data scientists charge between $35 to $200 per hour. As you could imagine, you get what you pay for. High-end data scientists that are able to use various programs and get projects done in a timely manner will cost more money. That being said, do not underestimate the knowledge of a new DS who has an updated skill set.
Fixed Payment Plan
Hourly rates can be intimidating, especially if you are not sure how quickly they’ll get the project done. Some people are concerned that freelancers will take more time than they should. If you want to settle for a fixed price, then you should expect to spend about $2,000. Larger projects will require more money, but it is more than worth the business insight.
Full-Time Data Scientist
If you are not interested in freelance data scientists, then you’ll have to spend quite a bit more money to keep one hired full-time. Most data science jobs have to get paid between $75,000 to $110,000 per year. It is a steep expense, but it can grant you quite a bit of money in the long run. Knowing how customers and clients interact with your product is incredibly valuable.
Getting a data scientist on your team provides excellent results. If you are able to fit the expenses into your budget, you’ll be more than happy.
Are you trying to find out why someone would want to hire a data scientist? Learn the pros and cons in the following sections.
What Are the Advantages of Hiring a Data Scientist?
Hiring a data scientist can improve profits, elevate the customers’ experience, and promote a happy work environment for your business partners and employees. There are many other benefits that you’ll be able to enjoy from hiring a data scientist, so do not shy away from it just because of the aforementioned expenses.
The advantages of hiring a data scientist are as follows:
- They’ll create tables for you to study and produce high-quality results for your company. Data scientists are able to take data and input it into an algorithm to make predictions of possible actions. You won’t have to test your customer base since you’ll have the estimates right in front of you.
- Data scientists are more reliable than traditional data plug-in programs. Instead of making predictions with stock algorithms, you can trust a data scientist’s knowledge and expertise, increasing the odds that you’ll achieve the desired results. It’s a much better course of action than pen and paper mathematics.
- Other businesses are more likely to trust information gained from a professional rather than questionable responses. If you claim that you hired a data scientist when submitting information, they’ll respect your numbers instead of wondering if they’re accurate. You’ll improve client-based relationships and trustworthiness.
- You can spend time doing other tasks rather than waiting around, figuring out which formulas to use. If you are able to present the data in a readable format, then data scientists will be able to dissect it and create tables for you to analyze quickly. Keep your attention on other important projects and let the pros handle the data.
- Some data scientists create the tables of info and tell you what you should do with it. Rather than having to spend time analyzing data, they’ll do all of the hard work and make suggestions to optimize your company. Note that these types of data scientists who go above and beyond typically require more pay.
You know all of the reasons that people want a DS on their team. The knowledge and valuable info get your business growing like never before. If there’s room in your budget, it’s not a bad idea to hire one for a short project before you hire full-time.
Are There Any Downsides?
As with all job hires, there are a few disadvantages of hiring a data scientist. Fortunately, none of them are deal-breakers for most companies. If you are interested, but you want to make sure you know all of the information before opening your wallet, you’re in the right section.
Check out the downsides of hiring a data scientist below.
- Perhaps the most common reason that people don’t want to hire a data scientist is the cost. Nobody ever claimed that data scientists are cheap; it is a huge reason that so many people are pursuing the career. Spending thousands of dollars is not something that’s appealing, especially to new companies.
- Some people mistakenly hire data scientists when they need a different professional for the project. According to Towards Data Science, it’s not uncommon for businesses to accidentally hire data scientists when they need statisticians, market analyzers, and engineers. Although data scientists have a similar skill set, it is not quite the same.
- Projects usually take longer than you’d hope. Data scientists are incredible at getting data and placing it into a traditional format that other people can read. However, these tasks can take months, weeks, or years, depending on how much data is being analyzed and placed into their algorithms.
- If there’s an error in the data, it could ruin projections. For this reason, many companies ensure that they pay top dollar to get the best data scientists on the market. Instead of risking your company and blowing the stat sheets, you’ll ensure good-quality work that has proven results.
There’s not much that could deter someone from hiring a DS once they learn how beneficial they can be. If these downsides haven’t scared you away, then it’s time to read on below to find out what you should look for when you’re interviewing and hiring a data scientist.
What Should You Look for When Hiring a Data Scientist?
You can’t hire the first data scientist that you come across, or you might end up sorry. There are thousands of freelance data scientists, but that doesn’t mean that all of them are worthy of being employed for every company.
Many data scientists have areas of expertise, which means they’re not so good at other parts of the job.
Here’s a list of five features to consider when you’re hiring a data scientist:
- Make sure that their expertise aligns with your needs. As mentioned above, data science is a broad field. They might be better with different algorithms, coding languages, and tables. Make sure that they can reach your expectations with past examples and so on.
- Always keep your budget at the front of your priorities. You’ve already read the part about budgeting and knowing how much it’ll cost you to hire a data scientist, but your budget should be unchangeable. Don’t adjust the amount you’ll spend, but keep your expectations realistic, so you don’t end up getting disappointed or offer low pay.
- Present the data in a usable format and ensure that they have the proper coding knowledge. Various programs can only be read in a certain format, so it’s important that you talk with the data scientist so you can get the results. Python, R, and many other types of coding can translate to a broad spectrum of readable information.
- Establish a timeline with the data scientist before hiring them to ensure that it’s within your deadline. Many data scientists have estimated timelines and other projects to tend to. If you’re hiring someone for a project that needs to be finished by a specified date, ensure that it works with the DS that you’re talking to.
- Learn about how long they’ve worked in the field, how they started out, and the different jobs they’ve completed. If they don’t have any prior experience, there’s a high chance that you’ll have to go back and forth. Note that beginner data scientists often charge less money, so that might work for your budget.
Knowing what to look for is equally as important as knowing if you should hire a data scientist in the first place. You could hire a random DS, but, chances are, you’ll end up getting results in an incorrect format or far too late. These rules will help you to create realistic expectations and high-quality results.
Are They Worth It?
Data scientists allow you to excel in your industry, but there are skeptics who might say otherwise. If you’re someone who prefers to outsource the tedious tasks in hopes of getting high-quality results, then you’ll find that hiring a DS is more than worth it. However, other companies don’t find them necessary.
So, is it worth it to hire a data scientist? Ask yourself these questions:
Does Your Company Have the Budget for a Data Scientist?
The first and most important consideration relates to the financial side of the commitment. If you cannot afford a data scientist, then there’s no way that it’s worth it. Furthermore, if you’re able to handle small tables by yourself without getting confused, then you might find that it can be handled in a timely manner.
Do You Have Plenty of Information at Your Disposal?
Data scientists require a bit of data to get them going. It depends on what type of information you’re seeking to find out. If you’re trying to learn why customers don’t make purchases on a certain page or why they’re walking out of your store without buying an item, data scientists will be able to use various details (walk-ins, impulse item placement, etc.) to their advantage.
How Reasonable Are Your Deadlines?
If you need something completed by tomorrow, then there’s a good chance that you won’t be able to find a DS in time. Many of them are working on multiple projects, which means they won’t be able to jump on your task right away. It’s best to have a couple of weeks of fluff to let them finish your project and make it worth the investment.
Other considerations include whether or not they excel in your field, how often they work, and so on. In the end, hiring a data scientist is worth it for almost every company that can afford it.
What Can a Data Scientist Do for Your Company?
Knowing the worth of a potential business partner or employee is all about what they can do for you. In this section, we’ll analyze the various tasks that a data scientist can do for your company in hopes that you’ll be able to make the decision.
Here’s a handful of jobs that a data scientist can handle for your company:
- They can extract data from various sources. If you want to know how many people click on a product vs. how many of them purchase it, then a data scientist can pull this information for further use.
- A data scientist can take the aforementioned information and create graphs, tables, charts, and other useful tools for you to use. You’ll be able to use these results to optimize your company and create a better solution.
- They clean data for your company. Didn’t you know that data’s always unclean? There are countless bugs and useless information that clouds it all up, which means a data scientist will have to spend a lot of time removing this excess information to make it easier for you to view.
- If you’re not sure where to start, many data scientists will be able to find the beginning point. All you have to do is tell them the desired results, and they’ll be able to find the info from a pool of data. It’s quite interesting how efficiently a data scientist can complete a task without needing too much information.
- Data scientists are also very good at coding to an extent. They have to use all sorts of coding languages, including the previously mentioned Python, and R. Java is another common coding language used by a plethora of data scientists, which is important because it’s one of the most common formats.
Data scientists can almost always do anything that relates to data. If you need to know how to improve your output and input, then a data scientist will be able to contribute in a way that allows your company to profit. You’ll make more than enough to pay the DS in the long run, so why not give it a try?
Data Scientist Hiring Checklist
Having a checklist lets you know the worth of a potential career partner, but it also helps you create a budget, plan for the future, and decide what you’ll do with the data. If you’re reading this article for the checklist, then you’re in luck.
Without further ado, here’s your promised data scientist hiring checklist:
- Perform a background check for previous employers. It’s important to know if they’ve worked with the format that you’re dealing with. Whether it’s tables and graphs or Python and R, your potential client should have knowledge and experience in the field.
- Set a budget before you begin the interviewing process. If you have a set price in your mind of $3,000, then there’s no need to exceed it. Start by suggesting $2,000 to the client, then go back and forth until you agree on a price. Never exceed your budget, or you’ll end up feeling like you made a mistake.
- Create a deadline with the data scientist. We’ve already covered the importance of adhering to deadlines, so there’s no need to go into detail about this checkbox. Just know that you need to be set in stone and ensured by the client that they can get it done.
- Go over the data and formulate a plan. This step might be the most important of all of them. The data scientist needs to know what their end goal is, and you need to make sure that you’re going to be happy with the results. Establish what info they need, how they can get it, and how they’ll submit the project when it’s complete.
- Follow up with the DS and stay in touch. Hiring a data scientist isn’t the end of the project; it’s the beginning! Contact them a couple of times per week, so you know they’re on task. Many companies prefer to make a series of milestones that are submitted weekly.
Did They Go to College or Pursue Online Courses?
Data scientists have two paths that they can follow to start their careers:
- Get a college degree.
- Go through an online boot camp course.
It’s important for you to know what route they chose, so you’re aware of their expertise. People who chose to go through college have a broader knowledge base of coding and data science. However, they’re not always current on the most updated formats. College classes cover the most popular formats, but they get outdated over the course of two to four years.
On the other hand, someone who chose to go through an online boot camp will have the most up-to-date knowledge of popular coding, tables, and more. However, they won’t have a wide knowledge-base about data science with a bit of computer science focus as a college graduate would.
Needless to say, the most advantageous option is to hire a data scientist who got a college degree in the field and followed up with an online course. Fortunately, this process isn’t as rare as you’d think. A lot of data scientists do both so that they can separate themselves from the rest of the competition.
Common Mistakes to Avoid
Unfortunately, a lot of companies make mistakes when they’re hiring their first data scientist. Whether it’s choosing the wrong candidate or setting unrealistic goals, you don’t want to get caught up in the nonsense.
Here are a few common mistakes that you can avoid:
- Towards Data Science states that not planning or setting goals is one of the most common issues that people run into. They want data and tables, but they don’t know what it should be about, how much it’ll cost, or when they can receive the information.
- Outsourcing the hiring process to people who don’t know where to start. If you’re able to manage a bit of time, interview, and hire the data scientists without an assistant. Meet them and decide if they’re the right person for the job.
- Trying to save money by hiring the cheapest data science will always be a mistake. People want to save cash, which is reasonable, but you’ll end up causing more headaches than you should’ve. Spend a bit more to get a whole lot more data.
- Don’t wait too long to hire a data scientist. If you’ve been shuffling through various blog posts trying to figure out whether or not you should hire a data scientist, why not give it a shot? You’ll thank yourself later when you have all of the information that you’ve been looking for.
Conclusion
Data scientists can provide all sorts of value for your company. You’ll be able to make the best decisions moving forward with the best knowledge on the market. Whether you’re dealing with advanced data science or low-level algorithms, a DS can be an invaluable investment for your business.
Most people who hire data scientists are more than happy that they made the commitment. As long as you’re able to get the proper data to the right DS, you’ll get the results that you’re looking for. Remember that you need to set reasonable deadlines, a fair budget, and stick with your commitments. A schedule with milestones is an excellent solution.
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
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