Job Description

About This Role

The Product Manager – AI / Analytics will play a critical role in shaping and delivering Carrier’s next generation of analytics, AI/ML, GenAI, and Agentic AI products. This role partners closely with executive stakeholders, engineering, data science, and analytics teams to define strategy, prioritize investments, and deliver scalable AI-powered products that drive measurable business outcomes.

This leader will own the product vision and roadmap end-to-end, lead delivery across globally distributed teams, and serve as a trusted partner to senior business leaders. The ideal candidate brings a strong analytics background, deep understanding of modern AI capabilities, and a bias toward action—moving quickly from concept to value while designing solutions that scale across the enterprise.

Key Responsibilities

Product Strategy & Roadmap Ownership

• Define and own the product vision, strategy, and multi-year roadmap for AI, analytics, GenAI, and Agentic AI products aligned to business priorities

• Identify and prioritize high-impact use cases across domains such as Supply Chain, Manufacturing, Service, Commercial, and Corporate Functions

• Develop compelling business cases, value hypotheses, and success metrics to guide investment decisions and measure outcomes
• Executive Engagement & Stakeholder Leadership

• Drive executive-level business conversations, translating complex analytics and AI capabilities into clear value narratives and decisions

• Act as a strategic partner to business leaders, ensuring AI and analytics products are tightly aligned to operational and strategic goals

• Balance competing priorities across functions and regions, ensuring transparency, alignment, and strong governance

AI / Analytics Product Delivery

• Lead cross-functional delivery teams spanning data engineering, analytics engineering, data science, ML engineering, and GenAI engineering, across multiple geographies

• Own and manage the product backlog, ensuring well-defined epics, features, and user stories that deliver incremental value

• Partner closely with engineering teams to guide solution design, trade-offs, and sequencing—ensuring speed, quality, and scalability

• Drive delivery of:

• Advanced analytics and BI products

• AI/ML models (predictive, prescriptive, optimization)

• GenAI solutions (e.g., copilots, knowledge assistants, summarization, Q&A)

• Agentic AI workflows that automate multi-step business processes with appropriate controls

Scale, Adoption & Value Realization

• Ensure products are designed for enterprise scale, reliability, security, and governance

• Drive adoption and change management, embedding AI and analytics into business workflows

• Monitor product performance using KPIs, user feedback, and business impact metrics; continuously refine roadmap based on outcomes

• Partner with platform, architecture, and governance teams to align with enterprise standards and responsible AI practices

Leadership Mindset & Ways of Working

• Lead with an entrepreneurial mindset—embracing ambiguity, experimenting quickly, and learning through iteration

• Balance speed and innovation with disciplined product management and scalable architecture

• Foster a culture of ownership, accountability, and collaboration across global teams

Required Qualifications

• High School Diploma or GED with 10+ years of experience in analytics, data, or AI product management

OR

• Bachelor’s degree with 5+ years of experience in analytics, data, or AI product management.
• Must be a U.S. Citizen or U.S. Permanent Resident
• This role can work anywhere in the US

Preferred Qualifications

• Strong knowledge of data analytics, business intelligence, and modern data platforms
• Demonstrated ability to partner with engineering and data science teams to deliver data and AI solutions
• Proven ability to influence stakeholders and drive alignment across cross-functional teams
• Familiarity with Agile and product-focused delivery methodologies
• Hands-on involvement in the delivery of AI/ML, Generative AI, and Agentic AI solutions within enterprise environments
• Working knowledge of modern data and AI technologies such as Snowflake, Databricks, AWS, and Power BI
• Understanding of MLOps, LLMOps, AI governance, and responsible AI principles
• Ability to lead product initiatives across distributed or global teams; industry knowledge in manufacturing, industrial, or HVAC environments is a plus