PROJECT MANAGER - BANKING - DATA & AI

Duncan & Ross Consulting; Riyadh; On-site; SAR 350,000 - 550,000; Full time

Job summary

Duncan & Ross Consulting seeks an experienced Project Manager to lead a large-scale Data Lake Modernization program and AI use-case delivery for a banking client in Saudi Arabia. You will bridge data engineering, AI/ML, cloud, and business stakeholders to govern, manage risk, and realize business value across multi-vendor teams.

The role requires experience delivering AI/ML-enabled use cases in financial services, strong stakeholder engagement, and a proven track record in complex,

Qualifications

• Bachelor's degree in Computer Science, Data/Information Systems, Engineering or related field.
• PM certification (PMP/PRINCE2) required.
• Agile certification (CSM/SAFe) highly desirable.
• 7+ years of project/program management experience with 3+ years in data platforms or data lake programs.
• AI/ML-enabled use cases experience in banking/financial services preferred.

Responsibilities

• Own end-to-end planning, governance, and delivery of the data lake modernization program.
• Lead AI/ML use case workstreams for hyper-personalization and NBO with cross-functional teams.
• Define the roadmap for data platform migration and governance.
• Serve as primary contact for CIO/CDO/Head of Marketing/ Retail Banking and report to steering committees.
• Coordinate data engineering, data science/AI, cloud/infrastructure, analysts, and change management.
• Ensure alignment of data lake modernization with AI delivery and proper sequencing.
• Manage external vendors and cloud/data platform partners.
• Drive Agile/hybrid delivery, manage sprints and backlogs.
• Embed data governance, quality, and regulatory compliance (SAMA, PDPL).
• Track ROI and value realization from AI use cases.
• Identify, escalate, and mitigate risks; support change management.
• Prepare steering packs and business case tracking for leadership.

Skills

Stakeholder management

Agile delivery

Executive communication

Data governance

Risk management

Education

Bachelor's degree in Computer Science, Data/Information Systems, Engineering or related

Master's degree (MBA or technical) an advantage

Tools

JIRA

MS Project

Confluence

Power BI

Excel

Job description

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

• Bachelor's degree in Computer Science, Data/Information Systems, Engineering, Business, or a related field. Master's 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