Flintex Consulting Pte Ltd
Data Scientist (Project Lead)
Singapore, SGVor OrtVertragVollzeit
Veröffentlicht am 30. Sept. 2026
Diese Stelle wird in EN ausgeschrieben
Data Scientist – AI/ML Project Delivery
Key Responsibilities
- Manage end-to-end Data Science and AI/ML projects, from problem definition and planning through testing, deployment, and handover.
- Engage business stakeholders to understand requirements, challenges, and expected outcomes.
- Translate business needs into clear project scope, deliverables, tasks, and success criteria.
- Collaborate with Data Scientists, Engineers, Developers, and Technical Leads to deliver practical AI/ML solutions.
- Track project timelines, milestones, risks, issues, and dependencies.
- Coordinate user testing, production readiness, deployment, and operational handover.
- Present project progress, technical findings, and outcomes clearly to both technical and non-technical stakeholders.
- Maintain required project documentation, approvals, and stakeholder sign-offs.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related STEM field.
- 3+ years of relevant experience in Data Science/AI project delivery, Technical Business Analysis, Technical Project Management, or similar roles.
- Experience managing AI/ML or data-driven projects from requirements through production deployment.
- Good understanding of Agile/Scrum project methodologies.
- Familiarity with cloud platforms such as AWS, Azure, or GCP.
- Strong stakeholder management, communication, and problem-solving skills.
- Able to work independently and effectively with cross-functional technical teams.
Working Hours:
Monday to Friday, 8:30 AM – 5:30 PM
Rollenübersicht
Jobart
Vollzeit
Erforderliche Kompetenzen
AI/ML Project DeliveryEnd-to-End Project ManagementStakeholder Requirements GatheringProject Scope and Success Criteria DefinitionAgile/Scrum MethodologiesProject Timeline and Milestone ManagementRisk, Issue, and Dependency ManagementAI/ML Production Deployment CoordinationStakeholder ManagementTechnical and Non-Technical CommunicationCross-Functional Team CollaborationProblem-SolvingCloud Platforms (AWS, Azure, or GCP)Project Documentation and Approval Management
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