In the rapidly evolving world of artificial intelligence and machine learning (AI/ML), product managers play a pivotal role in shaping the future of technology. But what makes a good AI/ML product manager? To answer this question, we turned to an industry expert, Nitin Baliga, who has made significant contributions to the field and demonstrated exceptional leadership in AI/ML product management speaks to International Business Times about what it takes to become a successful AI/ML Product Manager.
A Strong Foundation in Technology and Business
Nitin Baliga, Sr. Director of Product Management at a top 3 US Retailer, has over 15 years of experience in product management, strategy consulting, and technology. His expertise in AI/ML applications for consumer search and B2C products has driven remarkable growth and innovation in the retail and technology industries.
According to him, a strong foundation in technology and business is crucial for AI/ML product managers. He emphasizes the importance of understanding the technical aspects of AI/ML while also possessing the business acumen to identify opportunities and drive results. “AI/ML product managers need to have a solid understanding of the technology to effectively collaborate with data scientists and engineers,” Nitin says.
“However, they also need to have a strong business sense to identify opportunities, prioritize initiatives, and drive measurable impact. “Nitin’s background in Electronics & Communications Engineering, with a minor in Computer Science, and his MBA from the Ross School of Business at the University of Michigan have been instrumental in his success as an AI/ML product manager.
Customer-Centric Approach
Nitin believes that a customer-centric approach is vital for AI/ML product managers. By understanding customer needs and pain points, product managers can develop AI/ML solutions that truly add value and enhance the user experience.
“AI/ML product managers should always keep the customer at the center of their decision-making process,” Nitin explains. “By focusing on customer needs, we can build AI/ML solutions that not only drive business growth but also improve the lives of our users.” He also emphasizes not getting carried away by technology and being judicious in how you use and apply it. “You don’t need a sledgehammer for a nail when a hammer would perfectly suffice.”
Nitin’s work exemplifies this customer-centric approach. As the head of Search Quality, he has led the development of AI/ML solutions that make it easier for customers to discover and find relevant products with minimal effort. His efforts have driven double digit growth in revenue in the past five years and increased Search’s share of total revenue to significant levels.
Collaboration and Leadership
Collaboration and leadership are essential skills for AI/ML product managers, according to Nitin. Product managers must work closely with cross-functional teams, including data scientists, engineers, designers, and business stakeholders, to develop and launch successful AI/ML products.
“AI/ML product managers need to be strong collaborators and leaders,” Nitin says. “They must be able to bring together diverse teams, foster a culture of innovation, and drive results in a fast-paced, dynamic environment. “Nitin’s track record of leading high-performing teams over the last 15 years demonstrates his exceptional leadership skills. He has led multiple teams of product managers, collaborated with cross-functional teams of 100+ members, and driven large-scale digital transformations for Fortune 50 clients.
Continuous Learning and Adaptation
In the ever-evolving field of AI/ML, product managers must be committed to continuous learning and adaptation. Nitin stresses the importance of staying up-to-date with the latest AI/ML trends, technologies, and best practices.
“AI/ML product managers must be lifelong learners,” Nitin says. “They need to stay curious, embrace new ideas, and adapt to change in order to stay ahead in this rapidly evolving field.”
Nitin’s achievements in AI/ML product management are a testament to his commitment to continuous learning and innovation. He has been awarded multiple patents for his work in search results personalization, contextualization, and new item discovery using event-based machine learning models.
In conclusion, a good AI/ML product manager requires a strong foundation in technology and business, a customer-centric approach, exceptional collaboration and leadership skills, and a commitment to continuous learning and adaptation. Nitin Baliga’s impressive career in AI/ML product management exemplifies these qualities and serves as an inspiration for aspiring product managers in the field.
