As our businesses become more digital, data plays a vital role in everyday work functions. And this goes beyond measuring sales or web traffic–there are teams throughout the organization that can benefit from tracking and processing data to ensure they’re meeting business objectives. Nearly every department–from marketing teams looking for metrics on ad performance to facilities technicians that want to streamline operations–can benefit from data analysis.
For digital native companies, you’ll typically find that they have an entire data department run by a chief data officer. These companies leverage dashboards and real-time metrics to make key business decisions and improve their bottom lines.
But for companies who are still undergoing a digital transformation, even hiring just one data scientist would be a major step in the right direction.
However, like many other highly specialized digital roles, finding the right data scientist can be a challenge. Here are a few things to consider before you post the job.
1. Do you know what you’re looking for?
One of the issues many companies experience is not knowing what they need. They know they need someone who can pull and analyze data but what does that look like in a role? Will this person report to one specific department or will they manage high-level information across the company?
A general overview of this role would be to collect, organize, and analyze large data sets, using software that is designed for the task at hand. The analysis then needs to be presented in a way that’s easy to digest and act on.
But the role can get more granular depending on the industry or department. This is why it’s important to know exactly what you need well before you start interviewing candidates.
2. Is your company ready?
Knowing you need a data scientist doesn’t necessarily mean you’re ready to hire one. There are several things you’ll need to outline first:
The salary
The data scientist role is in hot demand these days. Due to the demand and skill set of this role, the salary you pay might be outside what the organization would pay for talent at a similar level. For example, if you’re looking to hire a chief data officer, then you might need to offer them nearly double what the CMO or CFO makes. Research the market values thoroughly to make sure your offer will be competitive.The role
Because this role is so in demand, many data scientists (especially the good ones) are looking for opportunities where they can make their mark and grow. If you don’t have a solid outline for the job or have the systems and software in place to support the role, then you might find applicants passing on the opportunity.The strategy
Does your company have a solid data strategy? Do you know where you want to be in six months, one year, or five years with the company’s analytics? Do you know what problems you’re trying to solve using data? The more defined your strategy is, the more compelling the opportunity will be to an applicant.
And remember, success in this role is only as good as the data itself. If your company is processing worthless data, then your data scientist will be working with worthless insights. This creates a no-win situation they want to avoid.
3. Can you make an attractive offer?
Like any high demand critical role, the negotiating process for a data scientist can be tough. Make sure you’ve researched the market value of the role and levels of experience. Another thing to consider is industry-specific experience and how to compensate for it.
If you find yourself offering the role to a candidate for $100,000, are you prepared if they counter it with $140,000? In negotiating situations like this, if I really like the candidate, I’ll offer to split the difference for the first six months. If, after six months on the job, they’ve lived up to the role and proved their worth, then we’ll bump the salary up to the what they originally asked for. This is a great way to motivate the employee and ensure they’re a good fit for the organization.
Final word
The right data scientist can help you streamline operations, find ways to improve sales, and strengthen your company’s position in the market. This is not a role to take lightly. As our world becomes more digital, the data companies can leverage will continue to rise. It’s vital to have professionals in place who can help you make sense of this information. For small businesses, this may mean hiring a data scientist to manage projects across the organization. For larger businesses, this may mean building an entire data department.
Either way, when it comes to hiring a data scientist, you need to be prepared. Otherwise, your job postings will either go unanswered, or you’ll end up with the wrong individual in the wrong role. To avoid this, make sure you A) have a solid data strategy in place, B) you understand the ins and outs of the role and that you can show prospects that the company is ready to support it, and C) you have some serious negotiation tactics in your back pocket.