Job Vacancy at CRDB Bank PLC: Manager, Artificial Intelligence Portfolio Delivery – October 2026

Company: CRDB Bank PLC
Position: Manager, Artificial Intelligence Portfolio Delivery
Department: Data Management Office
Duty Station: Tanzania Head Office
Reporting To: Head of Data Management
Employment Type: Permanent
Number of Vacancies: 1
Application Deadline: 9 November 2026

1. About the Role

CRDB Bank PLC is seeking an experienced Manager, Artificial Intelligence Portfolio Delivery to lead the delivery of enterprise AI initiatives within its Data Management Office.

The role combines technical leadership, portfolio management, and AI governance to ensure high-quality, production-ready AI solutions that deliver measurable business value.

The successful candidate will lead Data Scientists and Feature Engineers, overseeing modelling, feature engineering, code quality, portfolio delivery, and collaboration with Machine Learning (ML) Engineering and Machine Learning Operations (MLOps) teams while maintaining independent validation and formal approval processes.

2. Key Responsibilities

2.1 Technical Leadership and AI Delivery

• Set the technical direction and delivery plans for Data Scientists and Feature Engineers.
• Align AI initiatives with business priorities, data readiness, and available resources.
• Translate business problems into modelling objectives, measurable acceptance criteria, and feasible technical solution designs.
• Lead the selection and review of statistical and machine learning methods before development begins.

2.2 Feature Engineering and Model Development

• Direct feature design, data transformation, and the development of reusable pipelines.
• Review data quality, lineage, data leakage risks, and consistency between training and production inputs.
• Review Python and SQL code, experiments, and pipeline designs.
• Ensure reproducibility, version control, automated testing, and peer review before technical handover.

2.3 Model Evaluation and Generative AI

• Evaluate model results using appropriate test splits, benchmarks, and error analysis.
• Assess model calibration, explainability, fairness, and robustness where relevant.
• Guide retrieval, prompting, and evaluation for Generative AI and bounded agent workflows.
• Ensure appropriate grounding, source permissions, tool limitations, and human oversight.

2.4 AI Engineering and Production Readiness

• Resolve complex modelling and feature-pipeline problems through hands-on analysis, code reviews, and targeted prototyping.
• Define technical handover requirements with ML Engineering and MLOps teams.
• Ensure consistency in model scoring, interfaces, performance, monitoring, and rollback readiness.
• Review model drift, model quality, and feature quality with Model Owners.
• Recommend remediation or retraining and ensure material changes follow the required approval processes.

2.5 Portfolio and Stakeholder Management

• Manage portfolio scope, resources, budgets, dependencies, and supplier technical deliverables.
• Report on quality, delivery risks, milestones, and benefits against agreed baselines.
• Coordinate business acceptance and adoption with business owners and the AI Business Analyst & Adoption role.
• Distinguish measured business value from projected benefits.

2.6 Leadership and Capability Development

• Set staff objectives and review the technical performance of Data Scientists and Feature Engineers.
• Coach specialists and strengthen technical capabilities.
• Establish and improve standards for model development, feature engineering, experimentation, coding practices, documentation, and quality assurance.
• Promote innovation, knowledge sharing, technical mentoring, and continuous learning.

2.7 Governance and Compliance

• Maintain complete development evidence, document limitations, and address validation findings without replacing independent validation with internal team reviews.
• Collaborate with Data Engineering, ML Engineering, MLOps, ICT, Architecture, Cybersecurity, and business stakeholders to support successful delivery and operational readiness.
• Support compliance with the Bank’s AI Governance Framework, Model Risk Management Standards, Data Governance Requirements, Responsible AI Principles, and applicable regulatory obligations.
• Monitor portfolio performance, delivery milestones, technical risks, resource utilization, and dependencies, implementing corrective actions where necessary.
• Evaluate emerging AI, machine learning, feature engineering, analytics, and Generative AI techniques to identify opportunities for improving business value and delivery effectiveness.

3. Qualifications and Experience

3.1 Academic Qualifications

Applicants must possess a Bachelor’s degree in one of the following fields:

• Computer Science
• Data Science
• Statistics
• Mathematics
• Artificial Intelligence
• Machine Learning
• Data Engineering
• Engineering
• Analytics
• Information Systems
• Another related quantitative discipline

Added Advantages:

• A Master’s degree in Data Science, Artificial Intelligence, Machine Learning, Statistics, Computer Science, Engineering, Analytics, Business Analytics, Technology Management, an MBA, or a related field.
• Professional certifications in Artificial Intelligence, Machine Learning, Data Science, Cloud Computing, Data Engineering, Agile Delivery, Project Management, Product Management, or related disciplines.
• Relevant advanced AI, data engineering, or cloud certifications. Delivery-related certifications will also be an advantage.

3.2 Professional Experience

Candidates must demonstrate:

• At least five years of hands-on experience in Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics, Feature Engineering, or Data Engineering.
• At least three years of experience leading Data Scientists, Feature Engineers, analytics teams, or complex AI and data delivery initiatives.
• Strong Python and SQL programming skills, statistical knowledge, model evaluation expertise, and feature-pipeline development skills.
• Proven ability to conduct code reviews and troubleshoot technical problems.
• Experience delivering predictive AI, Generative AI, reproducible experiments, reliable pipelines, and monitored production solutions.
• Experience working with cloud platforms, modern data platforms, MLOps practices, version control systems, experiment tracking tools, and collaborative software development environments.
• Strong knowledge of statistical modelling, machine learning algorithms, feature engineering, model monitoring, explainability techniques, bias assessment, and model lifecycle management.
• Ability to challenge technical designs, mentor specialists, and balance technical quality, delivery priorities, costs, and business outcomes.

3.3 Preferred Industry Knowledge

Experience in banking or financial services will be an added advantage, particularly in the following areas:

• Digital banking
• Customer analytics
• Fraud detection
• Credit risk
• Collections
• Financial crime analytics

4. Key Competencies

The ideal candidate should demonstrate:

• Strong technical leadership and mentoring capabilities.
• Excellent analytical and problem-solving skills.
• Ability to manage multiple AI initiatives and competing priorities.
• Strong portfolio planning, resource management, and delivery coordination skills.
• Knowledge of responsible AI, model risk management, and data governance.
• Ability to collaborate effectively with technical teams and business stakeholders.
• Commitment to continuous improvement and innovation.

5. CRDB Bank’s Commitment

CRDB Bank PLC is committed to sustainability and Environmental, Social, and Governance (ESG) practices and encourages applicants who share this commitment.

The Bank promotes an inclusive workplace and encourages applications from women and persons with disabilities.

Important Notice: CRDB Bank does not charge any fees for the application or recruitment process. Applicants should disregard any requests for payment, as these do not represent the Bank’s recruitment practices.

Only shortlisted candidates will be contacted.

6. Employment Details

Item	Details
Position	Manager, Artificial Intelligence Portfolio Delivery
Department	Data Management Office
Reporting To	Head of Data Management
Location	Tanzania Head Office
Employment Type	Permanent
Number of Vacancies	1
Application Deadline	9 November 2026

7. How to Apply

Interested and qualified candidates should submit their applications through the official CRDB Bank Careers Portal before the deadline.

CLICK/TAP HERE TO APPLY:

Application Deadline: 9 November 2026