QNB3788 - Vice President Data Analysis

About QNB Established in 1964 as the country’s first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region. QNB Group’s presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines. QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor’s (A), Moody’s (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications. Based on the Group’s consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine. QNB Group has an active community support program and sponsors various social, educational and sporting events. Job Summary The Vice President – Data Analysis will lead the execution of QNB’s enterprise-wide analytics strategy, ensuring insights-driven decision-making across all business units. This role involves overseeing the development of executive dashboards, KPI frameworks, performance analysis, and business intelligence solutions that drive measurable business value. The incumbent will manage a team of analysts and collaborate across functions to improve profitability, enhance operational efficiency, and ensure compliance with internal and regulatory standards. It is ideal that the candidate should have: Advanced SQL and data modeling, Python, DWH / Lakehouse Design, ETL / ELT Pipeline Development, BI and reporting platforms, Data quality and reconciliation, Banking data domain knowledge, Workflow orchestration and automation, Databricks or similar, Data governance. Main Responsibilities • Shareholder & Financial: • Lead and manage a team of analysts, BI developers, and MIS experts with clear performance objectives and KPIs. • Define team OKRs aligned with strategic initiatives across business segments and digital transformation • Define enterprise-level KPIs, measurement standards, and performance dashboards aligned with QNB’s strategic and financial objectives. • Lead data-driven financial modelling, profitability analysis, and scenario planning to support C-level decisions. • Optimize business outcomes by integrating advanced analytics into key revenue-generating areas such as lending, deposits, and fee income. • Align analytics investments with organizational priorities and deliver maximum ROI from BI platforms and tools. • Design and deliver cost-efficiency analysis for operational processes using benchmarking and variance analysis. • Contribute to strategic initiatives such as Net Promoter Score (NPS) growth, client retention, and cross-sell analytics. • Monitor and analyse the impact of pricing, interest rate, and commission changes using dynamic models. • Evaluate and mitigate financial risk exposure through data-supported key risk indicators (KRIs) and early-warning models. • Act within the limits of the powers delegated to the incumbent and delegate authority to the respective staff and monitor exercise of the same. • Demonstrate clear understanding of the important factors behind the bank's financial & non-financial performance. • Customer (Internal & External): • Serve as a senior advisor to business units by converting data into insights to drive customer-centric strategy. • Collaborate with stakeholders across retail, corporate, international, and digital banking to deliver customized performance reports. • Lead strategic engagements with marketing, CRM, and product teams to optimize campaign effectiveness and client segmentation. • Oversee analytics initiatives that drive onboarding, retention, upselling, and loyalty programs. • Support branch/channel performance tracking and digital adoption strategies through channel-level analytics. • Ensure availability of real-time dashboards and alerts for business users through self-service BI environments. • Facilitate quarterly business reviews with senior executives using insight-backed reporting packs. • Build external partnerships with vendors and service providers for benchmark studies and advanced analytics solutions. • To assist customers in all their queries on Bank’s product and seek solution to their requests. • Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. • Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. • Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. • Internal (Processes, Products, Regulatory): • Own and govern the enterprise data analytics lifecycle from requirement gathering to insight delivery and refinement. • Design and deploy standardized business metric definitions and metadata repositories to support consistency across departments. • Lead cross-functional working groups to address analytics use cases across finance, risk, treasury, operations, and compliance. • Implement analytics frameworks to monitor and improve operational efficiency and cost optimization projects. • Ensure regulatory-compliant data architecture and reporting workflows as per QCB, GDPR, and NDCP. • Review, validate, and approve critical business models (profitability, risk scoring, churn) before deployment. • Work closely with the Data Governance and Quality teams to ensure audit readiness of all analytical models and outputs. • Evaluate and implement workflow tools that integrate analytics seamlessly with business systems (CRM, core banking, etc.). • Continuous Improvement: [add if they have subordinates] Set examples by leading improvement initiatives through cross-functional teams ensuring successes. Identify and encourage people to adopt practices better than the industry standard. Continuously encourage and recognise the importance of thinking out-of-the-box within the team. Encourage, solicit and reward innovative ideas even in day-to-day issues. • Learning & Knowledge: • Build a learning roadmap for the analytics team, covering technical upskilling and business storytelling techniques. • Champion a culture of analytical curiosity and insight-driven decision-making across business users. • Establish a knowledge-sharing environment through analytics playbooks, case studies, and success metrics. • Initiate cross-training programs for analysts to support multi-domain exposure and professional development. • Stay current with evolving analytics trends, AI/ML tools, and cloud analytics capabilities in financial services. • Mentor senior analysts on translating business problems into analytical hypotheses and data solutio

Lead the execution of enterprise-wide analytics strategy; oversee development of executive dashboards, KPI frameworks, performance analysis, and BI solutions; manage a team of analysts; collaborate across functions to improve profitability, efficiency, and regulatory compliance; define team OKRs and enterprise KPIs; lead data-driven financial modelling, profitability analysis, and scenario planning; optimize analytics investments; design cost-efficiency analyses; contribute to NPS growth, client retention, and cross-sell analytics; monitor pricing and risk models; ensure governance and audit readiness; serve as senior advisor to business units translating data into insights; lead engagements with marketing, CRM, and product teams to optimize campaigns and client segmentation; oversee onboarding, retention, upselling, and loyalty analytics; support branch/channel performance tracking and digital adoption; ensure real-time dashboards and self-service BI; facilitate quarterly reviews with executives; build external partnerships for benchmarks; maintain SLAs and relationships with departments; provide data to auditors and risk/compliance; own enterprise data analytics lifecycle; standardize metrics and metadata; lead cross-functional analytics use-cases; implement analytics frameworks for efficiency and cost optimization; ensure regulatory-compliant data architecture; review and approve critical models; collaborate with Data Governance for audit readiness; evaluate workflow tools; drive continuous improvement and learning in the analytics team; develop a learning roadmap and promote analytical storytelling; foster knowledge sharing and cross-training.