Yesterday, the Harvard Business Review featured an article written by The Data Incubator’s Co-Founder, Michael Li, on how to retain your highly sought after data scientists. Check it out:
Data scientists are in high demand: McKinsey estimated that we will be facing a shortage of 140,000 to 190,000 data scientists by 2018. Employers have to be on top of their game to keep competitors from poaching their hard-won data science talent. At the The Data Incubator, we work with dozens of companies eager to hire data scientists from our fellowship program. But, as we explain to those employers, attracting and hiring great data scientists is only the first step: they also need to motivate and retain them. We’ve drawn up some best practices both from our own experiences as well as from those of our hiring partners. They fall into three main categories: Support, ownership, and purpose.
- Great data science is built on great engineering. Make sure you provide enough engineering support so that they can get their job done. Are your tools appropriate for the job? If your data scientists are mostly doing very high level aggregate analyses, they shouldn’t have to be writing low-level MapReduce each time. Are your tools fast enough? Slow data clusters make it hard for data scientists to iterate quickly and saps both their motivation and creativity.
- Invest in their education. Pay for additional training classes, either online or at a local university. Cover lunch so they can hold regular seminars to teach each other new tricks of the trade. Provide space to host meet-ups with academics and data scientists from other companies. This will show that the company and the team cares about them. As a side benefit, you’ll be building up your team’s skill set.
- Have data scientists spend time with business or product units to better understand the real problems they are facing. This will make them feel like a valued member of the team and will strengthen their analyses and understanding of your business. As a result, they will help make better products and deliver better services to your customers.
- Data scientists don’t exist in a vacuum. They’re part of a greater universe of peers collaborating in a large open-source movement. Many of the best tools (R, d3, weka, python) are open source. So allow your data scientists to install and use their favorite tools. Data scientists are creative and don’t want to be hamstrung by onerous corporate security protocols. Also, giving them the time and encouragement to contribute back to those open source projects gives them a greater sense of purpose and ownership. It’s also a great recruitment tool for attracting other data scientists by advertising the high calibre of work done at your firm.
- When open source alternatives are not available, you’ll have to buy or build your own tools. Involve data scientists with procurement on purchasing decisions and engineering on design decisions. For chefs, there’s nothing more frustrating than working with someone else’s dull knives. For data scientists, being forced to use the wrong tools feels the same and jeopardizes both their morale and tenure.
- Recognize data scientists for their accomplishments. A good data scientist is able to take terabytes of data from multiple sources and synthesize it into a single pithy graph. Make sure you credit them for their hard work. Even better, let them present their findings to upper management. After all, no one knows the analysis better.
- Like many technical employees, data scientists are motivated by solving challenging problems. If they are performing repetitive weekly reports, allow them to work with engineering to automate these tasks. Find interesting new questions for your data scientists to work on. Ask your data scientists to come up with their own questions. Engage them to work on compelling data sets. This will not only keep them mentally sharp, but also engaged with the company.
In today’s market, good data scientists are getting recruiter calls every day. Employers need to work extra hard to keep them excited and motivated about staying where they are.
See the Article at HBR’s blog here: https://hbr.org/2014/11/retaining-your-data-scientists