Data Scientist (Project Lead - Data Science/AI) IJO

Location: Marina One

Core Focus Areas

. End-to-End Delivery Leadership: Managing the full project lifecycle from initial problem definition, scoping, and milestone tracking to user testing, production deployment, and project closure.

. Stakeholder Engagement & Vision Alignment: Engaging directly with business stakeholders to understand pain points, shape project goals, and communicate complex outcomes in a business-friendly manner.

. Business-to-Technical Translation: Converting high-level business vision and challenges into precise project scopes, actionable tasks, clear deliverables, and defined success criteria.

. Cross-Functional Collaboration: Partnering closely with Technical Leads, Data Scientists, and Engineers to ensure proposed solutions are technically feasible and aligned with business needs.

. Risk Management & Governance: Proactively identifying and mitigating project risks, issues, and dependencies while ensuring required documentation, approvals, and operational handovers are completed.

Duties and Responsibilities:

Project Strategy & Business Requirements Elicitation:

. Engage directly with business stakeholders across various industry domains to deeply understand their pain points, operational challenges, and strategic objectives.

. Shape project goals and translate complex, high-level business challenges into clearly defi ned project problem statements, scopes, deliverables, and success criteria.

. Work closely with Technical Leads, Data Scientists, Engineers, and Developers to validate that proposed AI/ML solutions are technically feasible and structurally aligned with client requirements.

End-to-End Delivery & Execution Management:

. Lead end-to-end Data Science and AI projects, taking full ownership of problem definition, planning, progress tracking, resource coordination, and delivery.

. Adapt and apply modern project management methodologies (e.g., Agile, Scrum) tailored to the unique flow of AI and data science delivery.

. Guide solutions seamlessly through all maturity stages: from initial prototype and validation phases to user testing, production readiness, and official release.

Risk Management & Governance:

. Actively identify, track, and manage project risks, issues, assumptions, and cross-team dependencies, escalating critical matters appropriately to ensure timeline integrity.

. Manage required project governance, ensuring all essential documentation, formal approvals, and stakeholder sign-offs are obtained throughout the project lifecycle.

Stakeholder Communication & Value Articulation:

. Present project progress, technical findings, and final outcomes in a clear, accessible, and business-friendly manner to non-technical stakeholders.

. Continuously gather stakeholder feedback throughout the delivery cycle to refi ne project direction and maintain strong organizational alignment.

. Manage stakeholder expectations, facilitate cross-departmental alignment, and build consensus between business and technical teams.

Operational Handover & Project Closure:

. Coordinate smooth, formal handovers to business-as-usual (BAU), support, or operational teams following official release to ensure long-term solution sustainability.

. Conduct formal project closures, capturing key learnings and ensuring all technical and operational handshakes are completed smoothly

Qualifications and Experiences:

. Minimum Bachelor's degree in Science, Technology, Engineering, or Mathematics (STEM).

. Minimum 3+ years of progressive experience as a Technical Business Analyst, Technical Project Manager, Technical Product Owner, or in a similar delivery role supporting AI, data science, or data-driven products.

. Proven track record of managing the full AI or data science project lifecycle-from ideation and problem definition through development, testing, production deployment, and operational handover.

. Strong practical knowledge of project management methodologies, including Agile and Scrum, with demonstrated ability to adapt them specifically to AI/ML delivery.

. Familiarity with major cloud platforms and AI infrastructure (e.g., Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure).

. Highly proactive and accountable mindset, demonstrating strong ownership and the ability to operate independently with minimal supervision in a fast-paced environment.

. Exceptional stakeholder management, presentation, and communication skills, with a proven ability to bridge the gap between business leaders and technical engineering teams.

Interested applicants, please Email, and look for [HIDDEN TEXT]

Joanne Loo Sze Min

EA Personnel Registration Number: R26160686

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