THRIVE: A Conversation with Data Leaders

At Thrive: NYC Data Leaders, more than 40 data science leaders from various industries, and three guest speakers from Pitney Bowes, Monte Carlo, and Yelp came to our event to discuss essential topics when leading AI teams.

Topics included talent acquisition and retention, aligning AI with the business, and centralized versus embedded teams.Leaders discussed their successes and challenges leading AI teams while providing invaluable insights into best practices that leaders can apply to any organization. Our event gave attendees the tools to take their AI initiatives to the next level.

The event was an incredible success and served as a platform for attendees to share their experiences in leading AI initiatives, discussing best practices and strategies, and learning from each other.

The event was an incredible success and served as a platform for attendees to share their experiences in leading AI initiatives, discussing best practices and strategies, and learning from each other.

Talent Acquisition & Retention
The speakers shared great insights regarding talent acquisition and retention. They emphasized that it's essential to cultivate a culture of openness and collaboration, offering employees learning opportunities that will help them grow in their roles and allow them to take ownership of their projects.

In addition, Talent acquisition and retention are key to a successful team. When hiring, focus on people who can complement or add to the team's skill set, valuing leadership skills over individual contributor skills. Providing autonomy for teams will boost employee morale and help increase talent retention.

Centralized Versus Embedded Teams
Whether you need a centralized or embedded team structure is a decision that will ultimately depend on the needs and goals of your organization. The speakers discussed the advantages of centralized and embedded team structures, depending on each organization's unique needs and goals.

They emphasized that teams should centralize their data before decentralizing it throughout the organization to ensure that alignment between business needs and data team performance is achieved. Companies should consider what type of structure will work best to maximize efficiency and success.