Data science can be a bit of a lonely job. It’s a shortage specialty, so many data scientists may be the only ones employed by their company. But they still need to learn about what’s new and exciting in the data science world. I caught up with Josefin Rosén about communication, coaching and communities to find out more about what SAS data scientists are doing to build communities and share knowledge.
Josefin, give us an idea of how you spend a typical week.
I’m not sure there’s any such thing as a typical week. I usually spend quite a lot of time supporting the account teams, going with them to customers to support their discussions with my expertise and creating awareness around what they could do with their data. Other work varies. Last week, for instance, I did a presentation at a large event in Stockholm. I spent a lot of time preparing for that. Then there’s all the social media, making sure that what we’re doing is visible in the best possible way. I follow the hashtags related to my area, and to the events where I participated, to add to the discussions as well as start my own.
How have you seen the role of data scientists change as analytics becomes more prominent in the mainstream business of organizations?
I think data scientists have developed a broader role in organizations. More people inside the organization are listening to them. They are closer to the strategy and the decisions in the company because we tend to turn to data analytics when it comes to these areas. I think data scientists have moved from being quiet introverts, just coding and building models, towards being forced to become better at communication. We have also seen other parts of the organization moving towards data science, with even executives taking courses in AI.
So the use of analytics is spreading through organizations, and it is becoming more valued?
Yes, definitely. We know from our own programs that this is true. We see a lot of data scientists on courses, naturally. But we’re also training citizen data scientists, those who don’t necessarily have a data science background but want to know more about analytics. They are starting to develop a data science mindset and picking up on the theory and the methods. Many now even call themselves data scientists in their organization, and it is great to see the community of data scientists expanding like this.
What sort of support do you think the data science community would most welcome? What do you think is missing today?
I think the biggest challenge, especially for young data scientists, is getting their models into production. They’re good at coding and making great models, but they find it harder to know how to use the right channels to get them deployed. Not all of them are aware of the tools that they could use – for example, how an analytics platform could help. For instance, it would complement their way of working with data and sort the governance and monitoring for them, and they could still use open source tools. Apparently, a typical data scientist spends about 50% of their day waiting for the model to run. I think many are unaware of how much help a platform could be.
I think the biggest challenge, especially for young data scientists, is getting their models into production.
How could we help them to become more aware?
I think this is something that we need to make more visible for the data science community. It seems to me that many data scientists are a bit scared of large players like SAS. We talk about analytics for everyone, but that’s not necessarily a good thing for some data scientists. It could threaten their position as the ones with the knowledge of analytics. But if we can help them to broaden the use of analytics through a platform and expand their reach, then I think that would really help.
What impact do you see from communicating more externally?
For myself, I’ve learned a lot about communication and how to make myself stand out to be more visible. And I’ve also learned the importance of focusing on my main issue and concentrating on what I want to talk about. I know a lot more about a wide range of channels, and I’m also clearer about my role in the organization.
I can also see that I’m having an impact externally. I think that's very valuable for the company, because it helps to promote our knowledge. I was astonished at how much impact you can develop by posting on social media, especially LinkedIn. I am very selective on what I post on LinkedIn and what I post is almost always connected to my specialty and the personal profile have built. LinkedIn for me is strictly professional, and posts are well thought through. They “live” longer and are not as many as on Twitter. It really opened my mind to the potential of communication and knowledge sharing.
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Let's exchange on the latest SAS applications and solutions for Data Scientists. We are having a virtual live data science event coming up: ”SAS Virtual Data Science Experience” on the 3rd of March. Join us in your time zone on the 3rd of March. The live event starts at 07:00am UTC and will continue until 12:00pm.