Practical AI Building a data team
Jul 27, 2021
Learn about the essential elements of building a successful data team. Explore the unexpected skill gaps in new hires and the importance of versatility. Delve into the historical evolution of data teams, the challenges they face, and the shift towards diverse roles. Discover strategies for fostering a data-driven culture and enhancing cooperation between technical experts and stakeholders. Hear insights on effective human management, communication, and the integration of AI in various applications.
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Early AI Team Hiring Mistake
- Chris Benson hired data scientists for an AI team but overlooked crucial DevOps and deployment skills.
- This necessitated course correction and hiring for those missing skillsets later.
Matching Skills to Needs
- Consider job satisfaction when hiring data scientists for less glamorous data aggregation tasks.
- A mismatch between expectations and assigned work can lead to issues.
Data-Driven vs. Expert-Driven Cultures
- Teams without data-driven cultures often rely on expert opinions, which can be arbitrary.
- Data teams must demonstrate a better approach and convince stakeholders of its value.
