KennedyPearce are partnered with a Global leading digital agency firm, recruiting for a principal Product Manager to join the Data and AI product team working in a hybrid environment based in London. The business are responsible for the full end to end product life-cycle for some of the World's most exciting and fastest growing technology brands, developing innovative solutions for the way companies handle their data and performance.
Role
As the Principal Product Manager, you will be responsible for leading on the product management strategy and road-map for Data and AI innovation across a plethora of clients. The product management team will partner closely with teams across data science, machine learning, AI, and development squads, plus be responsible for overseeing junior product managers and analysts.
Responsibilities
- Oversee the entire life-cycle of AI products, from discovery and testing to final delivery, collaborating closely with data science/machine learning, customer, and software engineering teams.
- Gain a deep understanding of stakeholder challenges, particularly in relation to the outcomes of AI products.
- Manage the Product road-map for AI Products and Services, including ideation, refinement, and alignment with engineering, marketing, and sales teams. Collaborate with the Head of Product and other Product Managers to ensure the AI Product road-map aligns with the Global Product road-map.
- Continuously monitor AI product performance, using insights to recommend and implement improvements.
- Lead go-to-market (GTM) activities for AI products, working with Product Marketing teams to define and review marketing materials that support the go-to-market strategy.
Experience
- Demonstrated ability in product management roles, preferably a good portion of it designing and building enterprise software solutions.
- Experience with building client facing AI products from ideation to launch, especially those involving NLP.
- Ability to communicate complex AI/ML stories and our value proposition across the company and customers.
- Technical know-how and market understanding in the areas of AI/ML, analytics DBMS, Big Data stacks, BI/ETL technologies and SaaS software in cloud environments.