Data Scientist (Project Lead)

recruit express pte ltd; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Recruit Express Pte Ltd is seeking a Technical Project Manager to lead AI and data science initiatives across business units. You will partner with stakeholders, define objectives, scope, milestones, and ensure alignment between business needs and technical delivery.

The role requires strong Agile/Scrum experience, cloud familiarity (AWS/Azure/GCP), and excellent stakeholder communications. You will guide multi-disciplinary teams from discovery through production, with go-live handover and

Qualifications

• Bachelor’s degree or higher in Computer Science, Engineering, Data Science, Mathematics, Statistics, or another STEM discipline.
• 3+ years of experience in roles like Technical Project Manager, Technical Business Analyst, Product Owner, Delivery Manager, or similar in AI/data/tech.
• Experience managing projects across the full data science/AI lifecycle.
• Strong understanding of Agile and Scrum tailored to AI/ML environments.
• Exposure to cloud technologies (AWS/Azure/GCP).

Responsibilities

• Own the delivery of AI and data science initiatives from discovery to production and handover.
• Establish project plans, timelines, milestones, dependencies, and resources with clear progress visibility.
• Coordinate multidisciplinary teams across business and technology functions.
• Apply Agile, Scrum, or appropriate delivery approaches for AI/ML projects.
• Manage progression from PoC to production readiness and go-live.

Skills

Agile methodologies

Stakeholder management

Communication excellence

Translation between business and tech

Project planning & governance

Education

Bachelor’s degree in Computer Science, Engineering, Data Science or related STEM

Tools

AWS

Azure

GCP

Job description

Business Analysis & Project Definition

• Partner with business stakeholders across different functions and industries to understand business needs, challenges, and strategic priorities.
• Convert business requirements and complex problems into well-defined project objectives, scope, deliverables, milestones, and measurable success criteria.
• Collaborate closely with Data Scientists, Engineers, Developers, Architects, and Technical Leads to assess solution feasibility and ensure alignment between business expectations and technical capabilities.
• Help shape practical AI, machine learning, and data-driven solutions that deliver measurable business value.

Project Delivery & Execution

• Own the delivery of AI and data science initiatives from initial discovery and ideation through development, testing, deployment, and post-launch transition.
• Establish project plans, timelines, milestones, dependencies, and resource requirements while maintaining visibility of delivery progress.
• Coordinate multidisciplinary teams and ensure effective collaboration across business and technology functions.
• Apply Agile, Scrum, or other appropriate delivery approaches, adapting project practices to accommodate the iterative and experimental nature of AI/ML projects.
• Manage the progression of solutions from proof-of-concept and experimentation through user acceptance, production readiness, and go-live.

Risk, Issue & Governance Management

• Proactively identify and manage project risks, issues, assumptions, constraints, and dependencies.
• Maintain appropriate project controls and reporting, ensuring potential delivery impacts are identified and addressed early.
• Escalate significant risks and blockers to the appropriate stakeholders and drive resolution.
• Ensure project governance requirements are met, including documentation, approvals, decision records, and stakeholder sign-offs.

Stakeholder Engagement & Communication

• Serve as a key point of coordination between business stakeholders and technical delivery teams.
• Translate technical concepts, project findings, and AI/ML outcomes into clear, business-focused communications.
• Provide regular updates on project status, risks, milestones, decisions, and expected business outcomes.
• Facilitate workshops, discussions, and alignment sessions to resolve differing priorities and build stakeholder consensus.
• Gather and incorporate stakeholder feedback throughout the delivery lifecycle to ensure the solution continues to address the intended business need.
• Manage expectations effectively across senior business and technical stakeholders.

Go-Live, Handover & Closure

• Coordinate the transition of completed solutions into BAU, support, or operational teams.
• Ensure operational teams receive the necessary documentation, knowledge transfer, support processes, and technical handover materials.
• Work with relevant teams to confirm production readiness and post-implementation responsibilities.
• Lead formal project closure activities, including lessons learned, outstanding actions, documentation completion, and stakeholder acceptance.
• Capture key delivery insights and recommendations to improve future AI and data project execution.

Requirements

• Bachelor’s degree or higher in Computer Science, Engineering, Data Science, Mathematics, Statistics, or another relevant STEM discipline.
• At least 3 years of relevant experience in roles such as Technical Project Manager, Technical Business Analyst, Product Owner, Delivery Manager, or similar positions within AI, data, analytics, or technology environments.
• Demonstrated experience managing projects across the full data science or AI lifecycle, from discovery and requirements definition through development, testing, production deployment, and operational transition.
• Strong understanding of Agile and Scrum methodologies, with the ability to tailor delivery practices to AI/ML and data science environments.
• Exposure to cloud technologies and AI/data platforms, such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Strong organizational and problem-solving skills, with the ability to manage multiple priorities in a fast-moving environment.
• Highly self-motivated, accountable, and comfortable taking ownership of projects with limited day-to-day supervision.
• Excellent communication, presentation, facilitation, and stakeholder management capabilities.
• Ability to communicate effectively with both senior business stakeholders and highly technical teams, acting as a translator between business objectives and technical delivery.