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

RECRUIT EXPRESS PTE LTD; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

RECRUIT EXPRESS PTE LTD invites an experienced Technical Business Analyst / Technical Project Manager to lead AI and data science delivery for diverse enterprise clients at Marina One, Singapore.

You will shape requirements, drive end-to-end delivery, manage risks, and ensure smooth handovers to BAU, collaborating with data scientists, engineers, and business stakeholders.

Requires 3+ years in AI/data projects, Agile/Scrum fluency, and cloud platform familiarity.

Qualifications

• Bachelor's degree required in STEM with relevant domain knowledge.
• 3+ years of progressive experience in Technical BA / PM roles supporting AI/data-driven products.
• Strong knowledge of Agile/Scrum and AI/ML delivery.
• Familiarity with cloud platforms (GCP/AWS/Azure).

Responsibilities

• Engage with business stakeholders to understand pain points and strategic objectives.
• Translate business challenges into clear project scopes, deliverables, and success criteria.
• Collaborate with technical leads, data scientists, engineers, and developers to validate AI/ML feasibility.
• Lead end-to-end data science/AI projects from problem definition to production handover.
• Manage governance, risks, issues, and stakeholder sign-offs throughout the lifecycle.
• Present progress and outcomes to non-technical stakeholders in business-friendly terms.

Skills

End-to-End Delivery Leadership

Stakeholder Engagement

Vision Alignment

Business-to-Technical Translation

Cross-Functional Collaboration

Risk Management

Education

Bachelor’s degree in STEM fields

Job description

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.