Descriptions
SUMMARY
OVERVIEW
Job Description Reporting Line SENIOR MANAGER ADVANCED ANALYTICS AND MACHINE LEARNING Location Tanzania Head Office Department DATA MANAGEMENT OFFICE Number of openings 2 Job Purpose The Data Scientist is responsible for designing, developing, validating, deploying, and continuously improving data science and machine learning solutions that deliver measurable business value in banking, while complying with the Bank’s AI governance, model risk management, data governance, information security, privacy, and regulatory
REQUIREMENTS
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- The role ensures models and analytical solutions are accurate, explainable, fair, secure, well-documented, and fit for purpose throughout their lifecycle.
- Principle
RESPONSIBILITIES
- Design, develop, and implement predictive, prescriptive, and optimization models for priority banking use cases such as fraud detection, credit risk assessment, collections, customer analytics, and operational efficiency.
- Translate business problems into data science use cases, define success criteria with stakeholders, and ensure proposed solutions align with approved business objectives and governance
REQUIREMENTS
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- Perform data exploration, feature engineering, model training, testing, and performance evaluation using sound statistical and machine learning techniques.
- Prepare complete model documentation, including business rationale, methodology, assumptions, data sources, feature definitions, limitations, performance metrics, and implementation considerations, to support review, approval, audit, and regulatory scrutiny.
- Ensure models are developed and maintained in line with the Bank’s AI governance framework, model risk management standards, data governance
REQUIREMENTS
- , responsible AI principles, and applicable regulatory obligations.
- Support model validation and approval processes by providing transparent documentation, reproducible development artefacts, evidence of testing, and clear explanations of model logic, outputs, and limitations.
- Assess and mitigate risks relating to model bias, unfair outcomes, data quality, privacy, explainability, robustness, and misuse, and escalate material issues through the appropriate governance channels.
- Collaborate with Data Engineering, MLOps, IT, Risk, Compliance, Information Security, Internal Audit, and business teams to ensure controlled deployment, integration, monitoring, and change management for analytical solutions.
- Monitor models and analytical solutions in production for performance, stability, drift, fairness, and operational effectiveness, and recommend recalibration, retraining, rollback, or retirement where required.
- Maintain version control, traceability, and audit trails for datasets, code, experiments, model versions, approvals, and production changes in accordance with internal standards.
- Apply appropriate controls for data confidentiality, customer privacy, access management, and secure handling of sensitive information throughout the model lifecycle.
- Contribute to model inventories, periodic reviews, performance reporting, and governance forums by providing timely updates on model status, issues, risks, and remediation actions.
- Support experimentation with advanced techniques such as time-series forecasting, natural language processing, and deep learning where justified by business need, data readiness, and governance approval.
- Promote a culture of responsible, ethical, and evidence-based use of AI and analytics [...]
HOW TO APPLY
Use the application link below to open the official application form.
