ML Product Owner
Position Overview:

The ML Product Owner for the ML Insights Team is the business champion, product owner, and process lead for our machine learning insight initiatives. This role bridges the gap between data science and business adoption, driving intake and ROI discipline, portfolio and lifecycle management, stakeholder alignment, and scaled deployment of models that deliver measurable impact across the organization.

The ML PO partners with data scientists, engineering leads, business stakeholders, commercial leaders, and clinical operations to translate model outputs into business value, run a consistent project intake and delivery process, manage the data science project portfolio, and secure ongoing investment and sponsorship.

This position requires strong data and statistical literacy, familiarity with data engineering / data warehousing concepts, product and process discipline (including a lightweight scrum-master function), and the stakeholder management skills to drive consensus in ambiguous,



high-stakes environments where business teams may not yet understand AI's potential or have legacy skepticism.

Deep hands-on ML technical ability (building or tuning models, reading research papers) is not required — the team will support the PO on technical depth.

Essential Duties:
Include, but are not limited to:
• Own project intake: ask questions to surface the real business problem and requirements, and assess whether ML/statistical modeling is the right solution before it enters the pipeline.
• Act as a buffer against scope creep and ad hoc requests that bypass the intake process; set realistic expectations with stakeholders about ML project uncertainty and timelines.
• Ensure ROI is estimated at intake and revisited post-launch to confirm vigente impact; craft business cases and ROI narratives to secure sponsorship and funding.
• Define and maintain a consistent process for the project lifecycle: intake, ROI, Business Review Documents (BRD), r

📌 Product Owner (México)
🏢 ITJ
📍 México