Data Product Manager

About Qualifyze

Founded in 2019, Qualifyze is a leading company in supply chain compliance management in the Life Sciences industry, trusted by over 1,200 pharmaceutical and healthcare companies globally. Our digital suite of solutions connects manufacturers, suppliers, and a global network of more than 250 auditors and quality experts. With a track record of over 3,000 audits across 85+ countries and the largest and most accurate supplier network and data analytics tools, Qualifyze stands as the all-in-one partner for quality compliance and supply chain risk mitigation in the Life Sciences sector. After securing a Series-B funding in September 2024, Qualifyze is now focused on expanding to the US market.

What we are looking for

The Data Product Manager role will play a pivotal role in shaping and driving the evolution of our data capabilities and AI solutions. As we expand our value proposition into Data and AI, you will be part of a dedicated Engineering team, working closely with Data Engineers and Data Scientists to build our data infrastructure and AI/ML capabilities.

This position is crucial for enabling our scaling of data sources, managing data quality at scale, and driving the implementation of AI-driven solutions that bring business value. If you have a strong technical background and a passion for data-driven product management, this could be the perfect opportunity for you.

Main Responsibilities

• Define the product vision and strategy for data and AI-related projects, ensuring alignment with business objectives.
• Collaborate closely with engineering and data science teams to build and scale our data infrastructure and AI/ML capabilities.
• Prioritize and manage the product roadmap, including the preparation of initiatives, epics, and user stories for the team to implement.
• Drive the integration and management of various data sources, ensuring data quality, consistency, and accessibility.
• Serve as the main point of contact for stakeholders, translating business requirements into technical specifications and communicating the value of data and AI initiatives.
• Contribute to the adoption and implementation of AI/ML models and tools, such as ChatGPT, Amazon Bedrock, and other industry-specific solutions.
• Lead the team in maintaining a strong focus on business use cases and the practical application of AI solutions to solve real-world problems.