Product Manager, Data Science & Analytics, Manufacturing

About the position

Carrier Global Corporation, a global leader in intelligent climate and energy solutions, is committed to creating solutions that matter for people and our planet for generations to come. From the beginning, we've led in inventing new technologies and entirely new industries. Today, we continue to lead because we have a world-class, diverse workforce that puts the customer at the center of everything we do. The successful candidate will have ownership of driving critical initiatives for analytics and data products, interfacing with our leadership team to align priorities, while providing guidance to the internal teams on analytics strategy and delivery. Additionally, the candidate will deliver end-to-end data and analytics solutions that will scale and empower our users to deliver on Carrier's goals and mission.

Responsibilities

• Define, develop, and maintain the product roadmap for analytics data products in alignment with business goals.
• Collaborate with stakeholders to gather requirements, define use cases, and prioritize features to maximize value.
• Act as a liaison between business and technical teams, translating business needs into technical solutions.
• Work closely with data engineers, data scientists, and BI developers to ensure accurate implementation of analytics solutions.
• Drive the integration of data analytics solutions into business processes, ensuring scalability and reliability.
• Monitor and evaluate product performance using KPIs, user feedback, and business impact metrics.
• Own the backlog for analytics and data-related products, ensuring that user stories are well-defined, prioritized, and executed efficiently.

Requirements

• Bachelors Degree
• 7+ years of experience in analytics, data, statistics, Machine Learning, and/or AI delivery roles.

Nice-to-haves

• Experience working with cloud-based data platforms such as AWS, Snowflake.
• Proficiency in data visualization tools (ex. Power BI) and SQL.
• Experience at large companies with complex data landscapes and scale.
• Experience delivering scalable analytics solutions, ideation through deployment.
• Experience leading teams and managing individual contributors.
• Data warehousing and data lake experience.
• Strong background in enterprise data and technology principles and best practices.