Co-operative Bank of Kenya AI – QA Automation Engineer Jobs
Job Summary
Develop advanced analytics, machine learning and AI-driven solutions that support strategic decision-making, improve business performance and drive innovation across the Bank.
Transform complex data into actionable insights and production-ready AI models while ensuring compliance with responsible AI, model governance and regulatory requirements.
Key Responsibilities
Collaborate with business units, product teams and stakeholders to identify priority business challenges and define analytical solutions.
Analyze large and complex datasets to discover patterns, trends, risks and growth opportunities.
Translate analytical findings into actionable recommendations for management and business teams.
Develop, train, test and validate statistical, machine learning, optimization and generative AI models.
Apply robust, reproducible and scientifically sound methodologies throughout the model development lifecycle.
Establish model performance benchmarks, validation criteria and monitoring frameworks.
Ensure model fairness, explainability, transparency and compliance with responsible AI principles.
Implement appropriate human oversight and model risk controls throughout AI solution deployment.
Collaborate with Data Engineers and Application Engineers to deploy AI solutions using approved MLOps and LLMOps practices.
Design and execute experiments, pilot programs and post-implementation evaluations to measure business impact.
Monitor model performance, identify data drift and detect deterioration in predictive accuracy.
Recommend model retraining, recalibration, enhancement or retirement where necessary.
Maintain comprehensive model documentation, source code repositories and validation evidence to support governance and audit requirements.
Develop reusable analytical assets, machine learning frameworks and best practices.
Share knowledge and build analytical capability across business and technology teams.
Qualifications
Bachelor’s Degree in Data Science, Statistics, Mathematics, Actuarial Science, Computer Science, Economics, Engineering, Operations Research or a related quantitative discipline.
Relevant Master’s Degree is an added advantage.
Professional certification in Data Science, Machine Learning, Artificial Intelligence, Cloud Computing or Analytics is an added advantage.
Experience
Minimum four (4) years of experience in Data Science, Advanced Analytics, Machine Learning or Applied Artificial Intelligence.
Proven experience delivering analytical and machine learning solutions from business
problem definition through deployment and production monitoring.
Experience working with large datasets and enterprise analytics environments.
Experience in banking, credit risk, fraud analytics, collections, customer analytics or financial services is an added advantage.
Demonstrated experience supporting data-driven decision-making and business transformation initiatives.
Technical Skills
Machine Learning and Predictive Modeling.
Statistical Analysis and Hypothesis Testing.
Generative AI and Advanced Analytics.
Python and/or R Programming.
SQL and Database Querying.
Feature Engineering and Data Preparation.
Model Evaluation and Validation.
MLOps and LLMOps Practices.
Data Visualization and Storytelling.
Experiment Design and A/B Testing.
Optimization Modeling and Decision Science.
Data Mining and Pattern Analysis.
AI Governance and Responsible AI Principles.
Business Intelligence and Analytical Reporting.
Key Competencies
Data-Driven Problem Solving.
Analytical and Critical Thinking.
Machine Learning Solution Development.
Business Acumen and Decision Support.
Research and Innovation.
Communication and Data Storytelling.
Stakeholder Engagement and Collaboration.
Model Governance and Risk Awareness.
Attention to Detail and Quality Assurance.
Continuous Learning and Adaptability.
Project Planning and Execution.
Results Orientation and Accountability.
Preferred Attributes
Strong understanding of banking, financial services and digital transformation initiatives.
Ability to translate complex technical concepts into business-focused recommendations.
Experience with AI-powered decision systems and production analytics environments.
Passion for innovation, experimentation and continuous improvement.
Ability to balance analytical rigor with practical business value.
How to apply
For more information and job application details, see; Co-operative Bank of Kenya AI – QA Automation Engineer Jobs
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