Feature Engineering Specialist at CRDB Bank – September 2026

Job Vacancy

Company: CRDB Bank PLC
Position: Feature Engineering Specialist
Location: Tanzania Head Office, Dar es Salaam
Department: Data Management Office
Reporting To: Senior Manager – Advanced Analytics and Machine Learning
Number of Positions: 1
Job Type: Full Time
Employment Terms: Permanent
Application Deadline: 5 October 2026

Job Purpose

The Feature Engineering Specialist is responsible for designing, developing, testing, and continuously improving features and feature pipelines that support accurate and reliable machine learning solutions and deliver measurable business value in banking.

The role ensures that features—the data inputs used by machine learning models—are relevant, reusable, traceable, well documented, and consistent between model development and operational use throughout their lifecycle.

The position will also ensure compliance 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 maintain features and feature pipelines for priority banking use cases, including:
  • Fraud detection
  • Credit risk assessment
  • Collections
  • Customer analytics
  • Operational efficiency
• Translate business requirements into feature specifications in collaboration with business teams and data scientists.
• Define success criteria and ensure proposed features align with approved business objectives and governance requirements.
• Perform data exploration, cleaning, transformation, and statistical analysis.
• Handle missing values and outliers.
• Create meaningful features such as transaction patterns and customer activity measures.
• Apply feature selection and dimensionality reduction techniques to retain useful information, remove redundant inputs, and improve model efficiency and predictive performance.
• Build and maintain reliable and scalable feature pipelines with Data Engineering and MLOps teams.
• Ensure consistent transformation rules and feature values between model training and operational use.
• Test feature quality, accuracy, completeness, and availability.
• Prevent data leakage by excluding information that would not be available at prediction time.
• Retain reproducible evidence of feature testing.
• Prepare complete feature documentation covering:
  • Business rationale
  • Definitions
  • Data sources
  • Transformation rules
  • Assumptions
  • Limitations
  • Version history
• Ensure features and pipelines comply with the Bank’s AI governance framework, model risk management standards, data governance requirements, responsible AI principles, and applicable regulatory obligations.
• Assess and address feature-related risks involving data quality, bias, privacy, and stability.
• Escalate material issues through appropriate governance channels in collaboration with data scientists and control owners.
• Collaborate with Data Engineering, MLOps, IT, and data scientists to support controlled deployment, integration, monitoring, and change management for feature pipelines.
• Monitor feature pipeline stability, accuracy, and changes in input data.
• Investigate failures and inconsistencies and support timely remediation.
• Maintain a catalogue of reusable feature sets, version control, and traceability for source data and transformation code.
• Report the number of feature sets developed and available for reuse.
• Measure and report improvements in model performance attributable to feature engineering.
• Report feature pipeline stability and accuracy using agreed evaluation methods with data scientists.
• Apply appropriate controls for data confidentiality, customer privacy, access management, and secure handling of sensitive information.
• Share feature engineering practices that support responsible and evidence-based use of AI.

Qualifications and Experience

Applicants should have:

• Bachelor’s degree in:
  • Statistics
  • Mathematics
  • Computer Science
  • Data Science
  • Artificial Intelligence
  • Or a related field.
• Minimum 3 years of relevant experience in:
  • Data Science
  • Machine Learning
  • Feature Engineering
  • Data Engineering
  • Advanced Analytics
• Strong proficiency in Python and SQL.
• Practical experience in:
  • Data exploration
  • Data cleaning
  • Data transformation
  • Statistical analysis
  • Feature engineering
• Hands-on experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, or equivalent tools.
• Experience with feature selection and dimensionality reduction.
• Practical knowledge of:
  • Data pipelines
  • Big-data processing
  • Version control
  • Reproducibility
  • Feature monitoring
  • MLOps practices
• Good understanding of:
  • Data governance
  • Data quality
  • Model risk management
  • Responsible AI
  • Information security
  • Privacy
  • Applicable regulatory requirements
• Strong analytical and problem-solving skills.
• Strong communication and stakeholder-management skills.
• Ability to translate business requirements into effective feature solutions.

Added Advantage

Relevant professional certifications in any of the following will be an added advantage:

• Data Science
• Machine Learning
• Artificial Intelligence
• Cloud Computing
• Data Engineering
• MLOps

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 also states that it does not charge any fees for the application or recruitment process. Applicants should disregard any request for payment as it does 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

Employment Terms: Permanent

CLICK HERE TO APPLY