Past Event

THRIVE: A Conversation with Data Leaders

Align Data Science with Business Goals, Hiring & Retaining Your Data Talent, Centralized vs. Embedded ML Teams
New York, NY
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Irina Ashurova

Sr. Director of Data Development
Pitney Bowes
Irina led the BI team responsible for analyzing data and business requirements and providing reports and data visualization.

Shane Murray

Former SVP of Data and Insights @ The New York Times
Shane led the entire data organization at The New York Times and was responsible for the Data and Insights Team, heavily focused on the data platform.

Justin Norman

Former Head of Data Science @ Yelp
Experience leading 5 data science teams at Yelp, the corporate Data Product Management team, the Yelp DS/ML experimentation platform (Bunsen), and the Core Machine Learning Platform.
“We broke the siloes of the data teams by using data governance and data mesh to create a top-down approach to define our data domains coming from business needs.”
“Companies need to centrally build and mature their data team first before distributing it into the organization: centralize and then decentralize.”
“During the first 3 months, people develop an opinion of their new job and and colleagues. It's critical to guide new employees in that timeframe to align their technical skills and desired career prospects with your organization’s goals.”
“Embedding your data teams is a process that constantly evolves as new data products are required to meet business needs. To succeed, you need to keep alignment between the business side and the data team.”
“Managers should value leadership skills over individual contributor skills. Junior managers should focus less on what they're doing individually, and more on managing and improving their star team.”
“If you're onboarding talent from outside, you must do due diligence before starting the hiring process. This includes defining the role clearly and how it fits into the team, think about career trajectories, and design a smooth onboarding procedure to reduce training time.”
Get the key insights from the event

THRIVE: A Conversation
with Data Leaders


About the event

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.

Thank you for joining us!

25+ companies leading in data science joined us for our event.

Leadership Insights

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.

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