PROJECT MANAGER - BANKING - DATA & AI
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Key skills for this role
Role Overview
Lead end-to-end delivery of a large-scale banking data lake modernization program.
Deliver downstream AI use cases for hyper-personalization and Next Best Offer capabilities.
Bridge technical teams, business stakeholders, and senior banking client sponsors.
Key Skills for This Role
Full Job Posting
Job Purpose
Lead end-to-end delivery of a large-scale banking data lake modernization program.
Deliver downstream AI use cases for hyper-personalization and Next Best Offer capabilities.
Bridge technical teams, business stakeholders, and senior banking client sponsors.
Key Responsibilities
- Own project planning, governance, scope, timeline, budget, resourcing, risk, and issue management.
- Lead the AI/ML workstream for hyper-personalization and Next Best Offer use cases.
- Manage the roadmap for data platform migration, pipeline modernization, data governance, and AI model deployment.
- Coordinate data engineering, data science, AI, cloud, infrastructure, business analysis, and change management teams.
- Manage senior client stakeholders, steering committees, executive reporting, vendors, and technology partners.
- Drive Agile or hybrid delivery across sprints, backlogs, and release planning.
- Embed data governance, data quality, SAMA, and PDPL compliance requirements throughout the program.
- Track AI business value, support change management and readiness, and report risks and delivery status.
Required Qualifications
- Bachelor's degree in Computer Science, Data or Information Systems, Engineering, Business, or a related field.
- PMP, PRINCE2, or equivalent project management certification is required.
- Agile certification such as CSM or SAFe is highly desirable.
Experience
- At least 7 years of project or program management experience, including at least 3 years managing large-scale data platform, data lake, or data engineering programs.
- Experience delivering AI/ML use cases in banking or financial services is strongly preferred.
- Consulting experience with client relationships, steering committees, and multi-vendor delivery teams is required.
- Saudi or GCC banking experience and familiarity with SAMA requirements are strongly preferred or advantageous.
- Experience managing teams across data engineering, cloud infrastructure, data science, and business or marketing stakeholders is required.
- Experience with AWS, Azure, GCP, Snowflake, Databricks, lakehouse, or data mesh concepts is highly valued.
Skills and Competencies
- Strong understanding of data lake or lakehouse architecture, ETL/ELT pipelines, and data migration methodologies.
- Working knowledge of AI/ML concepts for personalization and recommendation systems.
- Strong stakeholder management, executive communication, Agile delivery, financial acumen, and risk management skills.
- Experience with JIRA, MS Project, Confluence, PowerPoint, and Excel.
- English fluency is required, while Arabic proficiency is strongly preferred.
Performance Indicators
On-time and on-budget delivery of data lake modernization milestones.
Successful production deployment and adoption of hyper-personalization and Next Best Offer use cases.
Improved offer performance, personalization engagement, cross-sell, and campaign ROI metrics.
Client satisfaction, effective risk mitigation, and minimal critical delivery delays or escalations.
Working Relationships
Internal relationships include data engineering, data science, AI, cloud, infrastructure, business analysis, change management, and practice leadership teams.
External relationships include client CIO, CDO, retail banking and marketing leaders, client IT and business teams, and technology vendors.
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