Key Responsibilities
- Lead the end-to-end delivery of data platforms, AI, and machine learning solutions-from data ingestion and preparation through model development, deployment, and monitoring.
- Collaborate with data scientists, data engineers, ML engineers, and business stakeholders to translate Data Analytics, Customer Experience, Decisioning, AI/ML use cases into actionable delivery roadmaps.
- Ensure best practices in data governance, model validation, versioning, and operationalization (DevOps).
- Drive adoption of cloud-native services and tools on Google cloud platforms or multi-platforms.
- Implement agile project management and DevOps automation tailored to data and ML workflows.
- Oversee risk management related to data privacy, regulatory and compliance, technical dependencies.
- Mentor and coordinate multidisciplinary teams focused on data integration, feature engineering, model training, and scalable inference pipelines.
- Measure delivery success through business OKRs and Technology KPIs e.g. DORA.
- Facilitate continuous improvement in Data project delivery frameworks and technical standards.
- Always drive/ support the adoption of Data Strategy and work in alignment with GCIO strategy and Global standards.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related fields.
- With solid years of technical delivery experience, with ideally some years leading large-scale projects (USD5M+) or data platform initiatives.
- Deep understanding of data engineering, machine learning lifecycle, MLOps, and cloud AI services (AWS, GCP, Azure).
- Must have positive, can-do attitude and needs to be a self-starter. Strong analytical and problem-solving skills, with the ability to identify issues and implement effective solutions quickly.
- Strong leadership and stakeholder engagement skills with the ability to communicate complex technical concepts to technical and non-technical audiences.
- Must be an excellent written and oral communicator with the ability to refine and create significant mandatory and ad hoc project documentation. Strong knowledge in JIRA, Confluence, ITSA, EHC, Data Visa etc. is preferred.
- Must be able to hit the ground running and is expected to deliver multiple concurrent programme and projects with minimal supervision.
- Proven experience in applying Agile practices to deliver projects effectively. - Certification in Agile methodologies (e.g., Certified ScrumMaster, PMI-ACP, SAFe) is a plus.
Preferred Qualifications
- Certification: Google Cloud Professional Data Engineer or relevant Data Engineering or AI Certifications (preferred).
- Experience in use of AI assist tooling for coding, test management.
- Good sense of industrial trend in Data, AI Technologies.
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