Project Manager - Data & AI

Project Manager Data & AI

Project Management & Delivery

• Manage the end-to-end lifecycle of Das, including planning execution, monitoring, and closure.
• Define project scope, timelines, budgets, and deliverables while ensuring alignment with business goals.
• Oversee the implementation of Data and AI/ML solutions, ensuring they meet quality standards.
• Identify and mitigate project risks, including technical challenges, data privacy concerns and scalability issues specific to AI/ML environments.
• Facilitate cross-functional collaboration, resolving conflicts and fostering a culture of innovation and continuous improvement.

Stakeholder Management

• Engage proactively with stakeholders across technical teams, business units and executive leadership to gather requirements, align expectations and ensure buy-in throughout the project lifecycle.
• Facilitate regular communication through status updates, steering committee meetings, demos, and progress reports tailored to different audiences.
• Translate business needs into clear technical requirements and bridge communication gaps between non-technical stakeholders and data/AI teams.

Risk & Quality Management

• Identify risks early and develop mitigation plans to avoid project delays.
• Ensure quality standards for data accuracy, AI model performance, and scalability are met.
• Conduct project retrospectives and implement lessons learned to improve future delivery.

Required Skills & Qualifications:

• Project Management:

  Proven experience managing large-scale Data & AI projects using Agile/Scrum methodologies.

• Technical Understanding:

  Knowledge of data engineering, data analytics, and machine learning workflows.
• Familiarity with

  Azure, AWS, GCP, Sagemaker, PowerBI

• Understanding of MLOps, RAG (Retrieval-Augmented Generation), and Generative AI concepts.
• Knowledge of data governance, AI ethics, and regulatory compliance.

• Certifications (Mandatory):

  PMP, PRINCE2, Agile/Scrum Master, or Cloud certifications (Azure/AWS/GCP).

• Soft Skills:

  Strong communication, stakeholder management, analytical thinking, and problem-solving skills.