Reporting Line
\nSENIOR MANAGER ADVANCED ANALYTICS AND MACHINE LEARNING<\/p>\n
Location
\nTanzania Head Office<\/p>\n
Department
\nDATA MANAGEMENT OFFICE<\/p>\n
Number of openings
\n1<\/p>\n
Job Purpose<\/p>\n
Responsible for designing, building, optimizing, and deploying machine learning (ML) models into production environments. The role bridges the gap between data science and operational systems by ensuring that models are scalable, secure, and performant.
\nPost a job<\/p>\n
Principle Responsibilities<\/p>\n
Develop, deploy, and operationalize\u00a0machine learning and deep learning models\u00a0in collaboration with data scientists and MLOps engineers.
\nBuild and maintain\u00a0model APIs, microservices, and serving infrastructures\u00a0for real-time and batch inference.
\nEnsure\u00a0model scalability, performance, and security\u00a0in production environments.
\nImplement\u00a0CI\/CD pipelines\u00a0for seamless integration, testing, and deployment of ML models.
\nCollaborate with data engineers to optimize\u00a0data ingestion, preprocessing, and feature engineering\u00a0for model readiness.
\nMonitor deployed models for\u00a0drift, accuracy degradation, and operational performance, implementing retraining pipelines as needed.
\nContribute to the design and maintenance of\u00a0ML infrastructure and containerized environments\u00a0using tools like Docker and Kubernetes.
\nWork closely with the\u00a0Data Governance\u00a0and\u00a0AI Governance\u00a0teams to ensure compliance with ethical, regulatory, and operational standards.
\nDocument ML processes, model configurations, and versioning for\u00a0auditability and reproducibility.
\nContinuously research and integrate emerging ML engineering practices and tools to enhance model lifecycle management.<\/p>\n
Qualifications Required<\/p>\n
Bachelor\u2019s degree in Computer Science, Data Science, Software Engineering, or a related technical field.
\n3\u20135 years of experience\u00a0in machine learning engineering, data engineering, or related roles.
\nProven experience deploying and maintaining ML models in production environments.
\nPractical knowledge of\u00a0API development,\u00a0DevOps tools, and\u00a0container orchestration.
\nFamiliarity with\u00a0MLOps pipelines, model monitoring, and version control systems (Git).
\nExperience working in\u00a0financial institutions or regulated environments\u00a0is an added advantage.<\/p>\n
CRDB Commitment<\/p>\n
CRDB Bank is dedicated to upholding Sustainability and ESG practices and encourage applicants who share this commitment. The Bank also promotes an inclusive workplace, hence applications from women and individual with disabilities are encouraged.
\nWork placements
\nIt is important to note that CRDB Bank does not charge any fees for the application or recruitment process, and any requests for payment should be disregarded as they do not represent the bank\u2019s practices.
\nOnly Shortlisted Candidates will be Contacted.<\/p>\n
Deadline
\n2025-12-24
\nRecruitment services<\/p>\n
Employment Terms
\nPERMANENT<\/p>\n
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