In a nutshell:
- Retaining talented data teams requires constant upskilling and improvement.
- Empower your team members to develop new skills in areas like apps, data science, AI/ML, and beyond.
Zohar offers insights in the video above, or read on for more!
Retaining talented data teams is a persistent challenge that all data leaders face in today’s dynamic environment. But what if there was a simple way to keep your top performers happy and engaged? How can data leaders retain their talented teams?
Offer Constant Upskilling and Improvement
Data leaders should focus on constantly helping their teams upskill, improve their capabilities, and take on new challenges. As long as they’re building their skills and improving, they’ll make more and more business impact — and you’ll also find that it’s easier to retain them. Empower your data team members to explore new skills in areas like apps, data science, AI/ML, and beyond.
Retaining top talent is all about nurturing constant growth. People want to feel like they are expanding their capabilities and making an increasing difference.
Stagnation is the Enemy of Retention
In today’s dynamic data ecosystem, no one wants to stand still in their careers; they want to move forward and advance.
A specific way you can help your data stars grow (and keep them around for longer) is to introduce them to machine learning and AI capabilities.
Try a free trial of Pecan yourself to see how easy it can be for your data professionals to add these capabilities to their skill set. And, of course, your organization will also gain all the business benefits of trustworthy, intuitive predictive AI.
Zohar Bronfman is the co-founder and CEO of Pecan AI, working at the intersection of machine learning, causality, and real-world decision-making. He holds two PhDs—one in computational neuroscience and one in the philosophy of science—bringing an unusually rigorous lens to applied AI. Zohar focuses on turning predictive models into systems that reliably change outcomes inside complex organizations. He is a frequent voice on the future of AI and decision intelligence, with appearances in top-tier tech and business media and on leading industry podcasts. His work bridges deep theory and execution, aiming to make artificial intelligence both more accessible and more consequential.
