Four tips for hiring the ideal data scientist for your business
Executives across the globe have become convinced that data science is the magical conduit to increased profitability, greater efficiency, lower risks and enhanced customer relationships for their businesses. It is true that your business could attain some or perhaps even all of these benefits from correctly interpreting and managing your data. However, it is only a possibility if you hire the right individual or team to implement the data collection and analysis.
So how do you find and hire the ideal data scientist for your business? Let’s discuss some tips for approaching the hiring process to increase your likelihood of finding the perfect candidate.
1. Understand the strengths and limitations of data science
When hiring a data scientist for the first time, it is common for executives to face disappointment. In many instances, the disappointment comes about because of their own unrealistic expectations – not because the data scientist who came onboard was necessarily a bad hire.
To avoid disappointment, it’s important for you to understand which problems data can solve, and which problems it cannot easily help with. Then create a realistic list of the problems you want your data scientist to address.
Data scientists could potentially help you do things like detect fraud or identify recurring themes and patterns in large datasets. If you’re interested in harnessing the power of data to solve these types of problems, you’re likely to be able to achieve your goals given the right hire(s) and enough persistence in working through the problems.
2. Get a clear understanding of the required skill set
The following are some of the things your prospective data scientist will probably need to have experience with:
- Gathering and organising data acquired from multiple platforms
- Discovering new sources of data that could be useful for addressing your company’s problems
- Storing and backing up data
- Machine learning
- Natural language processing
- Computer programs in languages such as R and Python
In addition to these, there may be other required skills or knowledge that are unique to your industry and market niche.
Once you’ve determined the specifics of the necessary skill set, be prepared to us this list to articulate your desired candidate’s job description.
3. Be willing to pay a small fortune
There is currently a global shortage of experienced and qualified data science professionals, so expect that you may encounter some difficulty in filling your open position for a data science professional. You no doubt understand the basic economic principle of supply and demand. When demand increases and supply is short, the price of a commodity can skyrocket.
In the global marketplace, data scientists are one of those hot commodities in high demand and short supply. In Australia, data scientists’ salaries are particularly high. For example, according to the Glassdoor career website, the typical data scientist in Sydney earns $116,000 per year. There are data science professionals whose salaries top $140,000 per year. If you’re lucky enough to find a candidate with the right personality and skills, expect to pay that individual a salary that falls somewhere within that range – or perhaps even more, if the situation warrants it.
4. Consider training and hiring a data scientist from within
One obvious solution to the talent shortage problem would be to train one of your current employees to do the required job. This could be ideal if you already have a knowledgeable team working in IT. Your likeliest candidate would be a team member who is known to be an outstanding communicator and an excellent problem solver.
If you’re already working with a talented software programmer who possesses these traits, determine if s/he would be interested in making a career change into data science. Then, once you’ve selected a potential candidate for this promotion, interview that person to see if s/he would be receptive to receiving additional training to acquire the skills necessary for the job.
Ideally, the company would pay for the candidate to obtain this training. If the candidate already holds a bachelor’s degree, the logical next step would be a masters online in data science or a closely related field such as analytics or machine learning. As an alternative, it could also be possible for a candidate to obtain the necessary skills and knowledge through certifications or massive open online courses (MOOCs).
If you plan to hire a data scientist soon, definitely consider these 4 suggestions as you begin your search. It will probably not be easy to find the ideal candidate, but your company is likely to benefit significantly if you do find the right person who can do the job.