Data Product Manager | Computer Vision & Machine Learning

Drive Strategic Alignment 

• →Partner with global commercial stakeholders across LATAM, US, and Mexico to enable product understanding, drive adoption, and unlock new Computer Vision use cases.
• →Act as a product evangelist—educating stakeholders on product capabilities, limitations, and roadmap.
• →Provide regular updates to customers and internal stakeholders on product adoption, model performance, and business impact. 

 Plan & Prioritize 

• →Own quarterly product planning in collaboration with Data Scientists, Data Analysts, Data Engineers, ML Engineers and software engineers.
• →Balance business visibility, technical improvements, and infrastructure evolution when defining priorities.
• →Continuously assess team capacity and delivery risk to ensure plans are realistic, achievable, and aligned with broader product and business strategy. 

Execute & Deliver 

• →Partner closely with engineering and data teams to execute the quarterly backlog and deliver high-impact Computer Vision capabilities.
  
  
• →Drive delivery of:
  New Computer Vision use cases
  Scalable and secure APIs
  State-of-the-art ML models
  Comprehensive BI visualization.  

• →Define Epics and High-Level Requirements (HLRs), leading refinement sessions with a strong focus on:
  Dashboard visibility
  User experience (UX)
  Model behavior and performance 

• →Lead Agile ceremonies, including daily stand-ups, sprint planning, reviews, and retrospectives. 
  
  
• →Track delivery and performance metrics, producing sprint summary reports with emphasis on:
  Team productivity
  Model metrics
  Usage and adoption trends 

Engage Stakeholders 

• →Maintain strong relationships with technical, commercial, and senior leadership stakeholders.
• →Present quarterly roadmaps and progress updates with clarity and confidence.
• →Proactively manage expectations by negotiating scope, timelines, and trade-offs across internal teams and customers. 

• Proven experience managing data or ML-driven products, ideally within Data Science Products.
• Strong understanding of the ML lifecycle, including data preparation, training, deployment, monitoring, and iteration.
• Ability to translate business problems into technical product requirements for ML and AI solutions.
• Exceptional written and verbal communication skills, capable of bridging business, engineering, and data science audiences.
• Fluent English and Advanced Spanish to collaborate effectively with global teams.
• Willingness to work on-site in São Paulo

• Solid background in Product Management or Data Product Management, preferably with ML/AI products.
• Hands-on experience writing Epics, High-Level Requirements (HLRs), and technical documentation—documentation is one of your strengths.
• Foundational understanding of software architecture, including databases, APIs, and ML models.
• Experience working in Agile environments with highly cross-functional teams (Data Science, ML Engineering, MLOps, Backend, Frontend).