Data Scientist (Project Lead - Data Science/AI)

JOB OVERVIEW:

The Data Scientist (Project Lead - Data Science/AI) serves as the critical bridge between strategic business vision and successful AI delivery. This role is dedicated to leading end-to-end Data Science and AI projects by translating complex business challenges, pain points, and requirements into clearly defined project objectives, actionable plans, and high-impact solutions.

By balancing strong business acumen with technical delivery leadership, the incumbent manages project risks, aligns cross-functional technical teams, and guides solutions across the entire project lifecycle—from ideation and prototyping to production deployment and official release. Ultimately, this role ensures seamless stakeholder alignment, high-quality execution, and the successful handover of scalable AI initiatives to operational teams.

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 defined 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 refine 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.