This is an excerpt from our newly released data science salary study, to download the full report with more detailed compensation data, demographic information, and how data science salaries compare to predictive analytics salaries, click here.
Although assertions about data scientists sometimes border on hyperbolic (I’ve yet to meet a newly-graduated data scientist earning $300,000+, for example) one thing is very clear: the demand for data scientists is rapidly increasing, and as a result, they are frequently contacted by recruiters.
In fact, in our recent flash survey of hiring managers for data science and analytics teams, we discovered that 89% of them are looking to hire in 2015. Additionally, our flash survey of data scientists revealed a high demand for these professionals: 96% say they are contacted at least monthly by recruiters and 31% are being contacted several times per week. Coupled with the well-reported shortage of quantitative professionals, this can make finding and hiring data scientists very difficult.
While we can’t promise that this advice will make hiring data scientists easy, there are several ways you can make your organization a more appealing environment for data scientists:
1. First, your organization must have a clear commitment to data driven decision making. Data scientists want to know that their employer is serious about data science and will allow them to keep up with the constantly evolving field. The last thing data scientists want is a role where they spend more time justifying the need for their work than doing the work itself. Now that data science has moved from the back room to the board room at many firms, data scientists will want to see top level buy-in, and know that their work influences decisions.
2. Hire a leader to lay out the road map and get your team in place. Fill in the team by recruiting thoroughly and aggressively, but also look internally for staffers interested in learning and adapting their skills.
3. Be ready to teach business skills. It is easier to teach business skills to a data scientist than it is to teach an MBA or general analyst all of the technical skills required to be a data scientist, as the skill set required to work with unstructured or streaming data to solve complex problems is time intensive and challenging. However, teaching business skills still requires proactive effort from management. Keep your data scientists updated with news, books, and articles about your industry. Invite data scientists to high level meetings, and always explain the full context of their work. Understanding the greater business objective is an invaluable learning opportunity, and it will lead to analyses that are tailored to your business’ priorities.
When hiring, develop clear criteria for evaluating candidates for data science jobs, and carefully screen candidates based on their skills – not just their titles. With the increase in media attention, there has also been a sharp increase in the number of professionals who label themselves “Data Scientist” without having the necessary skills. Since the pace of the market doesn’t appear to be slowing down any time soon, you may also need to fix your hiring process in order to successfully hire a talented candidate.
Interested in our salary research on data scientists and predictive analytics professionals? Download our studies using the button below.
Want highlights from our 2019 Data Science & Analytics report, including salaries, demographic comparisons, and hiring market analysis? Watch our 15-minute RECAP video below!