Learning to be a professional data scientist requires more than just math skills. It also involves developing social norms, networks, and getting acclimated to the context of work. With the shift to remote and hybrid work, new methods are needed for transmitting this information and culture. Intentional face time, skill transmission through collaboration, and purposeful networking can help develop new data scientists in this changing work environment.
Creating New Data Scientists in the Age of Remote Work
As a senior practitioner in the field of data science, I understand the challenges of becoming a professional data scientist. It’s not just about math skills, but also about social norms, developing networks, and getting acclimated to the context of our work. In the past, much of this learning happened through observation and osmosis, being around experienced data scientists and absorbing their knowledge.
However, with the shift to remote and hybrid work, we need to find new ways to transmit this information and culture. Remote work requires intentional efforts to develop norms, skills, and networks. It’s not impossible, but it does require thought and planning.
Norms
Workplaces provide cultural and social norms that we learn through observation. This includes business jargon, attire expectations, and social etiquette. In data science, there are specific norms for how we interact with our bosses, communicate about technical topics, and handle professional situations. These norms are essential for success, and they can be learned through intentional face time and explicit communication.
Skills
Workplaces also provide opportunities to learn tangible skills. As data scientists, we need to learn how to apply our knowledge to real-world business problems. This involves learning new algorithms, coding best practices, and other skills from experienced colleagues. Passive learning through observation and absorbing how others do things is a valuable way to acquire skills. It’s important to be open to learning from colleagues and recognizing our blind spots.
Networks
Workplaces also facilitate the creation of professional networks. Building relationships with colleagues is crucial for career development. These connections can help us find opportunities and make connections in the future. For junior data scientists, breaking into these networks can be challenging, especially in remote work environments. Intentional face time and social interactions during designated on-site meetings can go a long way in developing strong networks.
Where we Work
In the current work landscape, there are different ways of working: fully in-office, hybrid with intentional face time, hybrid with haphazard face time, and fully remote. For most data scientists, a hybrid approach with intentional face time is the most likely scenario. Fully in-office work is unlikely to return for many, as remote work offers flexibility and improved quality of life. However, intentional face time is necessary to achieve the benefits of norms, skills, and networks.
How to Do It
To successfully develop new data scientists in a remote work environment, we need to be intentional in our approach:
- Transmit norms and culture explicitly, rather than relying on passive absorption.
- Create collaborative working opportunities during intentional face time to facilitate skill transmission.
- Recognize the importance of social interactions for network development and allocate time for purposeful face time.
Employers need to adapt their strategies for bringing on entry-level data scientists and provide them with the tools to grow and succeed in the new work world. As established members of the data science profession, it’s our responsibility to acknowledge the changes and put forth the effort to identify what’s important and find ways to achieve our goals in this new environment.
For more insights and AI solutions, visit www.stephaniekirmer.com.
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