Project Manager Banking Data & Ai

Job Summary

Job Purpose

The Project Manager will lead the end-to-end delivery of a large-scale Data Lake Modernization program for a banking client encompassing both the technical migration/modernization of the data platform and the implementation of downstream AI use cases specifically hyper-personalization of banking products and Next Best Offer (NBO) capabilities.

The role requires strong command of both traditional data/infrastructure delivery and AI/ML-enabled business transformation bridging technical teams business stakeholders and senior banking client sponsors.

Key Responsibilities

• Own end-to-end project planning governance and delivery of the data lake modernization program including scope timeline budget resourcing and risk/issue management.
• Lead delivery of the AI/ML use case workstream for hyper-personalization and Next Best Offer coordinating data scientists ML engineers and banking product/marketing stakeholders.
• Define and manage the project roadmap covering data platform migration (legacy to modern data lake/lakehouse architecture) data pipeline modernization data governance and AI model deployment.
• Act as the primary point of contact for senior client stakeholders (CIO/CDO/Head of Marketing/Retail Banking) managing expectations steering committees and executive reporting.
• Coordinate cross-functional teams including Data Engineering Data Science/AI Cloud/Infrastructure Business Analysts and Change Management resources.
• Ensure alignment between the data lake modernization workstream and AI use case delivery sequencing dependencies correctly (e.g. data readiness before model deployment).
• Manage third-party vendors/technology partners (e.g. cloud providers data platform vendors) as required for the project.
• Drive adoption of Agile/hybrid delivery methodologies managing sprints backlogs and release planning for both data engineering and AI workstreams.
• Ensure robust data governance data quality and regulatory compliance (SAMA data privacy/PDPL) are embedded throughout the modernization effort.
• Track and report on business value realization from AI use cases (e.g. uplift in offer acceptance rates personalization engagement metrics campaign ROI).
• Identify escalate and mitigate project risks particularly around data migration integrity model performance and change adoption.
• Support change management and business readiness activities to ensure banking product and marketing teams can effectively operationalize NBO/hyper-personalization outputs.
• Prepare and present steering committee packs status reports and business case tracking for senior leadership and client sponsors.

Required Qualifications

• Bachelors degree in Computer Science Data/Information Systems Engineering Business or a related field. Masters degree (MBA or technical) an advantage.
• Project management certification such as PMP PRINCE2 or equivalent required.
• Agile certification (e.g. CSM SAFe) highly desirable given hybrid delivery approach.

Experience

• Minimum 7 years of project/program management experience including at least 3 years managing large-scale data platform/data lake or data engineering programs.
• Prior experience delivering AI/ML-enabled use cases in a banking or financial services context experience with personalization engines recommendation systems or Next Best Offer/Next Best Action is strongly preferred.
• Experience working within a consulting environment managing client relationships steering committees and multi-vendor delivery teams.
• Experience in the banking/financial services sector in Saudi Arabia or the broader GCC strongly preferred; familiarity with SAMA regulatory and data governance requirements is a plus.
• Proven track record managing cross-functional teams spanning data engineering cloud infrastructure data science and business/marketing stakeholders.
• Experience with cloud data platforms (e.g. AWS Azure GCP Snowflake Databricks) and modern data architecture concepts (data lakehouse data mesh) is highly valued.

Skills & Competencies

• Strong understanding of data lake/lakehouse architecture ETL/ELT pipelines and data migration methodologies.
• Working knowledge of AI/ML concepts relevant to personalization and recommendation systems (e.g. propensity modeling customer segmentation real-time decisioning).
• Excellent stakeholder management and executive communication skills able to translate technical complexity into business value for senior banking executives.
• Strong Agile/hybrid project delivery skills including backlog management sprint planning and cross-team dependency management.
• Financial and commercial acumen budget management business case development and value tracking.
• Strong risk and issue management capability particularly in complex multi-workstream technical programs.
• Excellent skills with PM tools (JIRA MS Project Confluence) and reporting/presentation tools (PowerPoint Excel).
• Fluency in English required; Arabic language proficiency strongly preferred given local client stakeholder engagement.
• Comfortable operating in a fast-paced consulting environment with high client visibility and multiple concurrent priorities.

Key Performance Indicators (Typical)

• On-time on-budget delivery of data lake modernization milestones.
• Successful deployment and adoption of AI use cases (hyper-personalization NBO) into production.
• Measurable uplift in personalization/offer performance metrics post-deployment (e.g. acceptance rate engagement cross-sell).
• Client satisfaction and steering committee feedback scores.
• Effective risk mitigation minimal critical delivery delays or escalations.

Working Relationships

• Internal: Data Engineering Data Science/AI teams Cloud/Infrastructure Architects Business Analysts Change Management Practice/Engagement Leadership.
• External: Client CIO/CDO/Head of Retail Banking & Marketing client IT and business teams technology/cloud vendors third-party AI/data platform providers.

Vertical:

Technology

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