How to Come Out on Data Science Top in The Data Scientist Hiring War

By Kimberly Cook |Email | Sep 16, 2018 | 33000 Views

Demand for data scientists is at an all-time high and will continue to be at record levels in the coming years while these professionals become more scarce.

As evidence, since 2012, the demand for data scientists in the U.S. has increased by 650 percent according to a LinkedIn Workforce Report. And a recent McKinsey & Company study predicts there will be around 250,000 vacant data scientist roles in the U.S. in less than a decade.

Employers desperately need a niche, high-end data science professionals to drive actionable insights from the ever-growing stores of data being collected on internal processes, customer behavior, product development, and more.

But hiring for this specialized tech role is challenging - even more so when you don't have the brand recognition that comes with competitors like Google. However, by reevaluating your current hiring process with a few simple strategies, you can better attract these in-demand data science professionals, reduce the time it takes to get this talent and retain these skilled experts for longer.

Do The Market Research & Offer Competitive Salaries
First and foremost, remember competitors across all industries are looking to hire for this in-demand role, meaning many will end up hoping to recruit the same talent. One way your business can stand out and attract talent is by offering competitive salaries.

While you might not be able to offer the expanded benefits packages that leaders like Google can offer, doing the market research and providing a competitive salary is key to netting the most qualified candidates in today's candidate-driven market.

For data scientists, the average salary range is between $130,000 and $210,000, according to Mondo's 2018 Salary Guide. If budget constraints are limiting your ability to provide a competitive offer, then evaluate whether you can reallocate funds from another, less pressing need, or if the executive team might be open to increasing the salary is provided with a report detailing the ROI of the role.

Reflect Your Needs Throughout Hiring Process
One of the most common mistakes hiring managers to make is following the traditional hiring process for highly-specialized tech roles. Asking candidates questions about past work experiences or having them complete an example problem on a whiteboard provides a limited look at the skills you're trying to evaluate. Relying solely on this information can increase the odds of making a costly bad hire.

Instead, focus on creating an environment that reflects what the day-to-day of the role looks like. Create several initial needs the role would handle and have a general solution in mind. By understanding the challenges you'll have the right hire working on, you can adjust the hiring process to incorporate these as tests and interview questions.

Although attracting talent can be the most pressing challenge, you also don't want to make the mistake of onboarding a bad hire just to be done with the process. Reflecting the specific needs you have for the role in the hiring process will help you make the right hire the first time around.

Offer an Improved Work-Life Balance
When looking to recruit data scientists who can help analyze your data, consider focusing on how you can provide an improved work-life balance for the tech professional that joins your organization. A recent survey by the Harvard Business Review showed that a prioritized work-life balance is the second most valued employee benefit, followed by medical benefits.

Expanding employee benefits to include work-from-home options, unlimited PTO, and more flexible scheduling will improve your brand's appeal and highlight what your business can offer in-demand Tech professionals that competitors might not be offering.

Know How to Sell the Opportunity
Well-known brands don't have to do the extra work of selling candidates on the role because their brand exposure does it for them. While your business may not be an instantly-recognizable brand, learning how to sell the job opportunity can be an extremely effective hiring strategy to net in-demand data scientists.

Identify what your company provides that competitors might not be able to and communicate this during the interview. If your business routinely hires from within, encourages autonomous work among the Tech team, or invests in various skills development opportunities for employees, let potential candidates know.

Not everyone thrives in environments at large tech companies. Clearly outlining the differentiators between your business and leaders like Apple in what you're able to provide, whether that's with work environments or internal growth opportunities, could help sway professionals to accept your offer instead.

Speak to The Company's Vision
When selling the opportunity to the right candidate, don't overlook the importance of explaining the company's vision and impact for the future. Data scientists have more control over the opportunities they accept, so they tend to be more selective. One major differentiator between employers is the company vision or product and whether candidates believe in the business and feel this is where they should invest the next ten or more years of their career.

As senior tech professionals with high-level degrees, data scientists want to work for a company with a vision or product they're passionate about, where they will be seen as a key player and be able to invest in and grow with the business.

If you're a smaller business with an innovative product or a medium-sized business disrupting your industry while pursuing a socially responsible goal, speak to these elements in both the job description and interview process, so professionals know this is an opportunity providing both meaning and a long-term future. It could be the difference between landing the professional you're after and settling for a professional that is available. 

The article was originally published here

Source: HOB