We examine what's important for data scientists in their careers, including challenging work, networking with peers, foreseeing their career path and creating a good work-life balance.
"Do you know what people want more than anything? They want to be missed. They want to be missed the day they don't show up. They want to be missed when they're gone."(Seth Godin)
I had two main motivations to write this article. First, I once heard a top executive saying that what Data Scientists want is like any other employees: they want a good salary. According to my experience, this is only the tip of the iceberg. This is like believing that what Astronauts want is a respectable pay and an office with a window (note that I don't mean Data Scientists are as rare as Astronauts).
Second, I would like to bounce off the excellent article
by Jonny Brooks-Bartlett on the reasons why Data Scientists quit their jobs. It made me realize to which point companies new to Data Science may have a limited view on what Data Scientists want. This article is targeted towards companies employing Data Scientists or planning to hire them. This will improve your chance of hiring the right talents and retain existing ones. I use the term Data Scientists which also include Machine Learning specialists and Statisticians.
Here is whatData Scientists want.
Work on challenging problems
As stated by Jonny Brooks-Bartlett:
"[...] the fact that expectation does not match reality is the ultimate reason why many data scientists leave"
You need to be clear and transparent on what you expect for the position you advertise.Highlight interesting challenges. You don't need to be Google or Facebook to have interesting problems to solve. You are hiring your very first Data Scientist and do not have any existing data infrastructure? Tell the candidate that she will have the chance to start from scratch and build a brand new solution.
As written by Brooks-Bartlett, don't let Data Scientists be the go-to people for anything related to data. At one of my previous employers, I was asked to provide results that other employees could easily achieve. My main feeling was that my skills were not leveraged. Do not advertise your job as Data Science if it is about Business Intelligence and Reporting. You will end up with frustrated employees.
I once had to work for one month on a project not related to Data Science, which in addition was both not interesting and not challenging to me. This was simply the catalyst I needed to look around and find another job. Feeding your Data Scientists with challenging problems to solve is the best way to keep them within your company.
Most Data Scientists are passionate about their job. They did not choose Data Science because it is trendy. They have not embraced the field because of their grades at school.They have chosen Data Science because they are passionate about it. They love data, machine learning and statistics. Most importantly, they want to be challenged. Keep this in mind to retain your Data Science talents.
Exchange and network with peers
Employees usually follow trainings such as project and people management as well as other internal courses. Data Scientists love to participate to conferences and workshop. This is the place where they can meet with peers and exchange on their work.
Data Scientists like to meet other colleagues from different companies and fields. They like to learn new use cases and discover new algorithms. This will also avoid your Data Scientists get isolated. Let your Data Scientists present their work during external events and you will reduce employee turnover.
Data Scientists are proud of what they do. They like to share the way they solve challenges: which data they use, the algorithm chosen and any particularity of the application. The advantages of Data Scientists presenting to workshops and conferences aresignificant. In addition to making a positive impact on the company brand, it will attract talents and reduce employee turnover.
(Fore)see their career path
In most companies,a default career path is defined. From Analyst you will move to Senior Analyst, Manager, etc. As this is a pyramid, not all Analysts will end up at the C-level. Also, even if it is feasible for everyone to become a manager, a significant proportion of your Data Scientists will prefer to become experts. Once your Data Scientists become experts, they will need to remain so. This is not easy, particularly in the constantly evolving field of Data Science. They will have to keep up with the new algorithms, tools and data ecosystems.
It is your role, as an employer, to put in place a career path that suits your Data Scientists. In addition to the possibility to become team lead, you can propose several evolutions and rewards. Data Scientists can become internal consultants on specific analytics projects. Involve them in the recruitment process of junior Data Scientists. Ask your talents to perform a technology watch ofdomains such as Deep Learning or Text Mining. You can't get a new FTE to work with your experienced Data Scientist? Get a Master student for a six month project. Even without salary increase there are always ways to reward your Data Scientists. Just be creative.
Have a good work-life balance
This point is not only driven by the lack of Data Scientists in Industry. The main driver is based on flexibility. Data Scientists are flexible in the way they work. Drawing assumptions, analyzing data, making conclusions and iterating. This is the very nature of Data Science: continuous R&D. Coming back to the notion of passion, Data Scientists are passionate people. While solving business challenges is exciting, your Data Scientists are certainly reading Machine Learning books, organizing meetups and participating to Kaggle competitions. Having the opportunity to extend their passion outside of the office is definitely a plus you should make sure your Data Scientists can afford.
Since Data Scientists need to be flexible in their work, they value flexibility from their employers. Propose flexible working hours. Allow working from home. Be comprehensive with children and family issues. The rule is simple: treat your Data Scientists the way you would like them to treat their customers, whether they are internal or external to the company.
Thanks to Tyler Thacher
for his feedback on a first version of this article.
Bio: Sandro Saitta
has 10 years of experience applying Data Science in industries such as Finance, Telco, Chemicals, Online Travel and FMCG. He is currently Chief Industry Advisor at the Swiss Data Science Center (www.datascience.ch). Sandro holds a PhD in Computer Science from EPFL and founded the Swiss Association for Analytics to promote Data Science in Switzerland.
The article was originally published here