Minimum qualification and Experience

• Bachelor's degree in Computer Science, Statistics, Data Science, Engineering
• SAS Coding – Required; hands-on experience writing, testing, and optimizing SAS code in real-world projects.
• DS2 – Advantageous; actual experience working with DS2 in production environments.
• API Concepts – Required; experience using APIs to interact with systems, such as calling a decision engine via API and testing outputs.
• Credit Risk – Advantageous; experience working with credit risk assessments, decision models, or credit strategies in practice.
• Relational Databases PostgreSQL – Required; experience working with relational databases, including writing queries.
• SAS Visual Analytics – Advantageous; practical experience using SAS Visual Analytics to create reports, dashboards, or conduct analysis
• SAS Intelligent Decisioning – Advantageous; experience using SAS Intelligent Decisioning to manage and implement decisioning strategies.
• Post graduate qualification advantageous

Position outputs/competencies

• Assess the requirements of new credit rules and strategies, determining the most optimal way to implement them within the decision system.
• Develop new credit rules and strategies for easy future maintenance and optimal response time from the decision engine.
• Use API software to call the decision engine and test if the developed rules and strategies align with the received requirements.
• Analyse the output data from the decision engine to confirm the correct implementation of rules and strategies in production.
•  Perform analysis on system logs, API logs, and data from other credit lifecycle systems to ensure they are functioning as intended and providing correct outputs.
• Build simple reports based on system analysis for early warning triggers and monitoring purposes.
• Analyse credit data to answer business-related questions.
• Understand the overall credit system flow and how it connects with the credit strategy and business rules.