1. Deepen your subject matter expertise
As a data scientist, you need to deepen your familiarity with the domain of a given problem and non concentrating on the "Data Science" components.
2. Align on security best practices
Security is a continuous practice that all data scientists should take seriously especially when it comes to the open-source tools. Since open source is such an integral part of the data scientist toolkit, it is crucial that practitioners keep up with patches, updates and vulnerabilities of their tools.
3. Contribute to open source
Open source is an ecosystem of collaboration that transcends geographical locations, time zones and organizations. Take time to engage with the community that has brought us so many of today's intergyral backend technologies, while also expanding your professional network in learning new skills.
4. Never Stop Learning
As a data scientist, you should keep on learning something new since the field keeps on changing and growing every time.
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