Team Lead, Data Science & AI Engineering, Vice President

The Team Lead – Data Science & AI Engineering will be part of the COO Data Hub and will play a key role in supporting strategic initiatives in building and maintaining AI/ML applications.

Key Responsibilities

• Technical & Delivery Leadership – Act as team lead for a small group of data scientists and AI/software engineers; provide technical direction, coaching, and mentoring to ensure high engineering and data science standards; own solution design decisions and review architecture, code, and model implementations; promote best practices in model development, MLOps, software engineering, and documentation.
• Productionisation & MLOps – Drive the transition of POCs and experimental models into production; design and implement MLOps pipelines covering CI/CD for models and data pipelines; manage model deployment, versioning, and rollback; monitor data drift, model performance, and operational health; ensure solutions are reliable, maintainable, and cost‑efficient in production.
• AI / ML Solution Development – Lead end‑to‑end delivery of AI and ML use cases, including data exploration and feature engineering, model development, training, evaluation, and validation; oversee model performance monitoring and retraining strategies; support model validation activities in line with internal model risk management and governance requirements.
• Cloud Engineering – Design and operate AI and data workloads on the Cloud Platform; leverage services such as BigQuery, Cloud Storage, Vertex AI, GKE, and related ML services; work closely with cloud and platform teams to align with security, IAM, networking, and operational standards.
• Stakeholder & Cross‑Team Collaboration – Act as a bridge between business, data science, engineering, cloud, and governance teams; translate business problems into well‑defined technical solutions and delivery plans; provide implementation guidance and technical input to multiple teams seeking to leverage GCP AI capabilities.

Experience Requirement

• 8+ years of experience in data science, software engineering, or related roles.
• Proven experience as a technical team lead or hands‑on manager for small teams.
• Strong track record of moving AI/data solutions from POC to production.
• Practical experience operating workloads in cloud environments, preferably Google Cloud Platform.
• Experience working in regulated or risk‑sensitive environments is a strong advantage.
• Strong programming skills in languages such as Python and JS.
• Solid understanding of data pipelines, analytics workflows, and software engineering best practices.
• Hands‑on experience preferred with GCP services (BigQuery, GKE, Vertex AI, IAM, monitoring), containerisation (Docker) and orchestration (Kubernetes), CI/CD pipelines, and Infrastructure as Code (e.g., Terraform).
• Familiarity with MLOps concepts and tooling.

Soft Skills & Competencies

• Strong leadership and mentoring skills, with the ability to guide and develop team members.
• Excellent communication skills, able to explain complex technical concepts to non‑technical stakeholders.
• Comfortable operating in ambiguity and driving initiatives with partial information.
• Structured problem‑solver with a data‑driven and pragmatic mindset.
• Autonomous, curious, and proactive, with a strong sense of ownership.