Delivery & Project Management Lead and manage client implementations, ensuring an exceptional end-to-end experience. Collaborate with stakeholders to groom and prioritize the product backlog. Work with the development team to ensure accurate effort estimation of backlog items. Build project schedules and roadmaps based on estimates and business priorities. Monitor and communicate project status on a regular, clear, and professional cadence. Identify, track, and remove blockers; escalate cross-team dependencies when needed. Ensure that all teams remain aligned on project details, timelines, priorities, and deliverables. Monitor performance against scope, timeline, and budget, ensuring successful project outcomes. Continuously refine and improve workflows, processes, and project management tools. Machine Learning / Data Science Delivery Support Coordinate workloads and tasks across Data Science and Machine Learning teams. Support planning for data preparation, feature engineering, modeling, and validation stages. Align model development timelines with business and product delivery cycles. Collaborate with ML/DS teams to track dependencies, risks, and required stakeholder input.



Support deployment of ML models into production environments, working with engineering teams. Ensure proper documentation, monitoring, and governance for ML-related deliverables. Bachelor's degree or equivalent experience as a Delivery Manager. Technical background with familiarity across software development lifecycles including Agile. Experience managing complex, cross-functional initiatives and distilling them into actionable plans. Exposure to Machine Learning or Data Science projects — delivery coordination, requirements, or implementation. Strong analytical and communication skills, with the ability to translate technical details for non‐technical stakeholders. Tenacious, self-directed professional who thrives in dynamic, fast-paced environments. Previous experience supporting Data Science, ML Ops, or AI-enabled projects. Familiarity with ML model lifecycle processes: development, validation, deployment, monitoring. Experience working with cloud platforms (AWS, Azure, GCP) and data engineering teams.

📌 Delivery Director (Data Science/Ml Experience)) (México)
🏢 Ntt Data
📍 México