CRDB Bank Plc is seeking a Manager, Artificial Intelligence Portfolio Delivery to lead the delivery of enterprise AI initiatives within the Bank’s Data Management Office, overseeing technical execution, AI governance, production readiness, portfolio management, and the development of Data Scientists and Feature Engineers.
Responsibilities
- Set 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, acceptance criteria, and technical solution designs.
- Lead the selection and review of statistical and machine learning methods.
- Direct feature design, data transformation, and development of reusable pipelines.
- Review data quality, lineage, data leakage risks, Python and SQL code, experiments, and pipeline designs.
- Ensure reproducibility, version control, automated testing, peer review, and production readiness.
- Evaluate model results, calibration, explainability, fairness, robustness, and Generative AI workflows.
- Define technical handover requirements with Machine Learning Engineering and MLOps teams.
- Review model drift, model quality, and feature quality, recommending remediation or retraining where required.
- Manage portfolio scope, resources, budgets, dependencies, supplier deliverables, risks, milestones, and business benefits.
- Coordinate business acceptance and adoption with business owners and AI adoption stakeholders.
- Set staff objectives, review technical performance, coach specialists, and strengthen technical capabilities.
- Establish standards for model development, feature engineering, experimentation, coding, documentation, and quality assurance.
- Maintain development evidence and support compliance with AI governance, model risk management, data governance, responsible AI, and regulatory requirements.
- Collaborate with Data Engineering, ML Engineering, MLOps, ICT, Architecture, Cybersecurity, and business stakeholders.
- Evaluate emerging AI, machine learning, feature engineering, analytics, and Generative AI techniques.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field; a Master’s degree is an added advantage
- At least five years of hands-on experience in Data Science, Machine Learning, or Artificial Intelligence
- 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 modelling, machine learning, feature engineering, and model evaluation expertise
- Knowledge of cloud platforms, data platforms, MLOps, version control, and experiment tracking
- Knowledge of responsible AI, model risk management, data governance, explainability, fairness, and bias assessment
- Portfolio planning, resource management, and delivery coordination skills
- Technical leadership, mentoring, and stakeholder collaboration skills
- Technical leadership and mentoring capabilities.
- Strong analytical and problem-solving skills.
- Portfolio planning, resource management, and delivery coordination skills.
- Ability to manage multiple AI initiatives and competing priorities.
- Strong Python and SQL programming skills.
- Statistical modelling, machine learning, feature engineering, and model evaluation expertise.
- Code review, technical troubleshooting, and pipeline development skills.
- Knowledge of cloud platforms, data platforms, MLOps, version control, and experiment tracking.
- Knowledge of responsible AI, model risk management, data governance, explainability, fairness, and bias assessment.
- Ability to challenge technical designs and balance technical quality, delivery priorities, costs, and business outcomes.
- Ability to collaborate effectively with technical teams and business stakeholders.
- Commitment to continuous improvement, innovation, knowledge sharing, and continuous learning.
Document Requirements
