Data Scientist at CRDB Bank – September 2026

Job Vacancy

Company: CRDB Bank PLC
Position: Data Scientist
Location: Tanzania Head Office, Dar es Salaam
Department: Data Management Office
Reporting To: Senior Manager – Advanced Analytics and Machine Learning
Number of Positions: 2
Job Type: Full Time
Employment Terms: Permanent
Application Deadline: 5 October 2026

Job Purpose

The Data Scientist will be responsible for designing, developing, validating, deploying, and continuously improving data science and machine learning solutions that deliver measurable business value in banking.

The role will ensure that models and analytical solutions are accurate, explainable, fair, secure, well documented, and fit for purpose throughout their lifecycle, while complying with the Bank’s requirements relating to AI governance, model risk management, data governance, information security, privacy, and applicable regulatory requirements.

Key Responsibilities

• Design, develop, and implement predictive, prescriptive, and optimisation models for priority banking use cases, including:
  • Fraud detection
  • Credit risk assessment
  • Collections
  • Customer analytics
  • 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.
• Perform data exploration, feature engineering, model training, testing, and performance evaluation using sound statistical and machine learning techniques.
• Prepare complete model documentation covering:
  • Business rationale
  • Methodology
  • Assumptions
  • Data sources
  • Feature definitions
  • Limitations
  • Performance metrics
  • Implementation considerations
• 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, testing evidence, and clear explanations of model logic, outputs, and limitations.
• Assess and mitigate risks relating to:
  • Model bias
  • Unfair outcomes
  • Data quality
  • Privacy
  • Explainability
  • Robustness
  • Misuse
• Escalate material issues through 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 of analytical solutions.
• Monitor models and analytical solutions in production for:
  • Performance
  • Stability
  • Model drift
  • Fairness
  • Operational effectiveness
• 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.
• 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.
• Provide timely updates on model status, issues, risks, and remediation actions.
• Support experimentation with advanced techniques such as:
  • Time-series forecasting
  • Natural language processing (NLP)
  • Deep learning
• Promote responsible, ethical, and evidence-based use of AI and analytics across the organisation.
• Support knowledge sharing and adherence to approved standards and practices.

Qualifications and Experience

Applicants should have:

• Bachelor’s degree in:
  • Computer Science
  • Statistics
  • Mathematics
  • Data Science
  • Or a related field.
• Minimum 3 years of experience in:
  • Machine learning
  • Statistical modelling
  • Data analysis
• Professional certifications in Azure AI, Data Science, MLOps, and Responsible AI are mandatory.
• Demonstrated experience in:
  • Machine learning
  • Data engineering
  • AI governance
  • Business value realisation
• Proficiency in Python and SQL.
• Proficiency with machine learning frameworks such as:
  • Scikit-learn
  • XGBoost
  • TensorFlow
  • PyTorch
• Strong understanding of:
  • Statistics
  • Probability
  • Data science principles
• Experience with data visualisation tools such as:
  • Tableau
  • Power BI
  • Matplotlib
  • Seaborn
• Familiarity with cloud-based machine learning solutions on:
  • AWS
  • Microsoft Azure
  • Google Cloud Platform (GCP)

Added Advantage

A Master’s degree in any of the following will be an added advantage:

• Data Science
• Artificial Intelligence (AI)
• Machine Learning
• Statistics
• Business Analytics
• MBA with a specialisation in Analytics

CRDB Bank Commitment

CRDB Bank is committed to sustainability and ESG practices and encourages applicants who share this commitment.

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

CRDB Bank states that it does not charge any fees for the application or recruitment process. Applicants should disregard any requests for payment as such requests do not represent the Bank’s recruitment practices.

Only shortlisted candidates will be contacted.

How to Apply

Interested candidates should submit their applications through the CRDB Bank Careers Portal.

Application Deadline: 5 October 2026

CLICK HERE TO APPLY