Position Overview

Zanaco Bank Plc is inviting applications from suitably qualified and experienced individuals for the following job aimed at contributing to the Bank's strategic vision, in the Digital Banking Division under the Digital Channel Development, Delivery & Big Data at Digital - Head office:

Role Description

Job Purpose: To design, develop, and deploy data science, machine learning AI models that drive innovation in Zanaco’s banking services. The role holder is responsible for turning vast amounts of transaction data into actionable insights, automated decision engines, and predictive features. This role works closely with the Solution Architect Senior Specialist to bridge the gap between complex mathematical modeling and production-ready software.

Job Responsibilities:

• Build, train, and validate predictive models for use cases such as fraud detection, credit scoring, customer churn, and personalized marketing.
• Collaborate with the Data team to build robust data pipelines and ensure high-quality data for training (ETL process).
• Implement Natural Language Processing (NLP) for automated customer support tools (chatbots) and document processing.
• Design and execute A/B tests and statistical analyses to measure the impact of AI-driven features.
• Work with the IT team to deploy models into a production environment via APIs (integrating Python-based models with Java/Spring Boot services).
• Continuously monitor model performance (detecting drift) and retrain models to ensure ongoing accuracy.
• Optimize and manage various database solutions, including NoSQL (MongoDB, ElasticSearch, Hadoop), in-memory databases (MemSQL, Apache Ignite), and relational databases (Oracle, MySQL).
• Write advanced SQL queries to extract, manipulate, and validate large datasets.
• Build predictive models using Python or R, applying best practices in statistical modeling.
• Any other duties as assigned by superiors.

Requirements

Qualifications & Experience:

• Full Grade 12 Certificate with 5 credits; including English and Mathematics.
• Bachelor’s Degree in Computer Science, Statistics, Mathematics, or Data Science. (A Master's Degree or specialized AI certification is highly preferred.)
• 2 - 5 years’ experience working in a fast-paced environment with AI and ML tools.
• Experience with designing and developing APIs with low response times and resource utilization for large data sets.
• Experience in designing highly scalable data processing pipelines.
• NLP & Deep Learning - Experience with Neural Networks and NLP frameworks.
• Experience with SQL and NoSQL databases; knowledge of Big Data tools (Hadoop, Spark) is an advantage.
• Experience building ETL (Extract, Transform, Load) processes or using tools like Hadoop.

Job Core Competencies:

• Generation of campaign and project performance reports with ability to understand marketing concepts.
• Data Analytics - Ability to do end-to-end programming in python/SAS to extract the results as required by the problem at hand.
• Ability to review and analyze complex data aggregations.
• ML techniques - Knowledge of Modelling based on large set of variables from varied sources.
• Good understanding of Natural Language Toolkit (NLTK), Matplotlib, TensorFlow, D3.js, KNIME, WEKA, Statistical Analysis System (SAS), Tableau.
• Preferred understanding of banking and financial data patterns and regulatory requirements for AI (Explainable AI/Ethical AI).
• Expert-level proficiency in Python (specifically libraries like Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy).
• Strong understanding of Probability, Statistics, and Linear Algebra.
• Detailed understanding of DB internals and schema design for various types of Data stores (RDBMS, NoSQL).
• Good understanding of AI, Machine Learning and Data Science.
• Possess analytical skills to debug issues and provide solutions.
• Leadership and Mentorship skills.
• Ownership and Accountability.
• Effective Communication.
• Problem-Solving and Critical Thinking.
• Collaboration and Teamwork.
• Adaptability and Flexibility.
• Time Management and Prioritization.
• Emotional Intelligence and Empathy.
• Continuous Learning.

• Build, train, and validate predictive models for use cases such as fraud detection, credit scoring, customer churn, and personalized marketing.
• Collaborate with the Data team to build robust data pipelines and ensure high-quality data for training (ETL process).
• Implement Natural Language Processing (NLP) for automated customer support tools (chatbots) and document processing.
• Design and execute A/B tests and statistical analyses to measure the impact of AI-driven features.
• Work with the IT team to deploy models into a production environment via APIs (integrating Python-based models with Java/Spring Boot services).
• Continuously monitor model performance (detecting drift) and retrain models to ensure ongoing accuracy.
• Optimize and manage various database solutions, including NoSQL (MongoDB, ElasticSearch, Hadoop), in-memory databases (MemSQL, Apache Ignite), and relational databases (Oracle, MySQL).
• Write advanced SQL queries to extract, manipulate, and validate large datasets.
• Build predictive models using Python or R, applying best practices in statistical modeling.
• Any other duties as assigned by superiors.

• Generation of campaign and project performance reports with ability to understand marketing concepts.
• Data Analytics - Ability to do end-to-end programming in python/SAS to extract the results as required by the problem at hand.
• Ability to review and analyze complex data aggregations.
• ML techniques - Knowledge of Modelling based on large set of variables from varied sources.
• Good understanding of Natural Language Toolkit (NLTK), Matplotlib, TensorFlow, D3.js, KNIME, WEKA, Statistical Analysis System (SAS), Tableau.
• Preferred understanding of banking and financial data patterns and regulatory requirements for AI (Explainable AI/Ethical AI).
• Expert-level proficiency in Python (specifically libraries like Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy).
• Strong understanding of Probability, Statistics, and Linear Algebra.
• Detailed understanding of DB internals and schema design for various types of Data stores (RDBMS, NoSQL).
• Good understanding of AI, Machine Learning and Data Science.
• Possess analytical skills to debug issues and provide solutions.
• Leadership and Mentorship skills.
• Ownership and Accountability.
• Effective Communication.
• Problem-Solving and Critical Thinking.
• Collaboration and Teamwork.
• Adaptability and Flexibility.
• Time Management and Prioritization.
• Emotional Intelligence and Empathy.
• Continuous Learning.

• Full Grade 12 Certificate with 5 credits; including English and Mathematics.
• Bachelor’s Degree in Computer Science, Statistics, Mathematics, or Data Science. (A Master's Degree or specialized AI certification is highly preferred.)
• 2 - 5 years’ experience working in a fast-paced environment with AI and ML tools.
• Experience with designing and developing APIs with low response times and resource utilization for large data sets.
• Experience in designing highly scalable data processing pipelines.
• NLP & Deep Learning - Experience with Neural Networks and NLP frameworks.
• Experience with SQL and NoSQL databases; knowledge of Big Data tools (Hadoop, Spark) is an advantage.
• Experience building ETL (Extract, Transform, Load) processes or using tools like Hadoop.