The African Export Import Bank (the "Bank”) was established in Abuja, Nigeria in October, 1993 by African Governments, African private and institutional investors as well as non-African financial institutions and private investors for the purpose of financing, promoting and expanding intra-African and extra-African trade. The Bank was established under the twin constitutive instruments of an Agreement signed by member States and multilateral organizations, and which confers on the Bank the status of an international multilateral organization; as well as a Charter, governing its corporate structure and operations, signed by all Shareholders. The authorized share capital of the Bank is Five Billion United States Dollars (US$5 billion). The Bank, headquartered in Cairo, the capital of the Arab Republic of Egypt, commenced operations on 30 September, 1994, following the signature of a Headquarters Agreement with the host Government in August, 1994. It has branch offices in Harare, Abuja, Abidjan and Nairobi.
Reference: SM-STPD-SDI-2025
Job Summary
- The Senior Manager, Strategic Data & Intelligence plays a critical role in driving the Bank’s transition into a data-powered Strategy organization.
- The role focuses on integrating data science, analytics, and AI/ML technologies into strategic planning, execution, monitoring, and evaluation processes.
- The incumbent will design and manage advanced analytics models, AI assets, scenario simulations, and predictive insights to support high-level decision-making by the President, Executive Management, and the Board.
- This position sits within the Strategy & Product Development Division, under the Strategy Data and Intelligence Unit.
Key Responsibilities
Strategic Data, AI & Analytics Leadership:
- Develop and manage a proprietary Strategic Intelligence Knowledge Base using AI, ML, and advanced analytics.
- Design, build, and deploy predictive models and simulations to identify risks, trends, foresight, and new strategic opportunities.
- Integrate generative AI and machine learning models into the Bank’s strategy planning, implementation, and performance tracking cycles.
- Run AI experimentation cycles, simulate economic and geopolitical scenarios, and generate insights to support organizational preparedness.
- Lead strategic insight generation by using data and AI to improve decision-making on development impact, project design, and investment strategy.
Development Impact Analysis & Predictive Modeling:
- Collaborate with the development impact team to improve impact assessment methodologies using AI algorithms and predictive analytics.
- Build custom tools for profitability analysis, segmentation, forecasting, optimization, and performance modeling.
- Enhance the Bank’s data-driven decision-making culture through AI/ML-based strategic diagnostics.
Strategic Planning & Board Engagement:
- Support the preparation of Board papers and strategy documents using data-informed insights.
- Generate reports on strategic foresight, scenario analysis, and AI-supported evaluations of emerging challenges and opportunities.
Organizational Integration & Operationalization:
- Partner with the Organizational Architecture team to design target operating models that integrate AI capabilities.
- Contribute to the planning team by generating actionable insights for business plans and market expansion strategies.
- Improve the Bank’s strategic responsiveness by identifying emerging risks and opportunities across industries and geographies.
Ethics, Governance & Responsible AI:
- Implement AI governance and ethical frameworks, ensuring transparency, fairness, and legal compliance.
- Promote a responsible use of AI and align AI initiatives with the Bank’s mandate and public interest.
Leadership & Collaboration:
- Lead a high-performing team of AI/ML professionals, driving a culture of continuous innovation.
- Collaborate across internal departments and with external partners to embed AI in core business functions.
Minimum Qualifications & Experience
Educational Qualification:
- Master’s Degree in Mathematics, Engineering, Computer Science, Data Science, Economics, Artificial Intelligence, or a related field.
- A PhD is preferred.
Experience:
- At least 10 years of experience in AI/ML, advanced analytics, statistical modeling, and data science, preferably in financial services or consulting.
- Strong leadership experience in deploying AI/ML models in production and enterprise settings.
- Solid understanding of AI architectures including Transformers, GNNs, GANs, RNNs.
- Hands-on experience with tools like PyTorch, TensorFlow, Hugging Face, SQL, Python, R, Spark.
- Expertise in data visualization tools like Tableau, Power BI.
- Strong command of forecasting techniques, neural networks, gradient boosting, regression models, etc.
- Deep understanding of data pipelines, infrastructure, and resilience in large-scale AI deployments.
- High proficiency in communicating complex technical ideas to senior stakeholders.
Method of Application
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