This role supports Loan Origination System (LOS) projects, with a focus on system testing, UAT preparation, credit rule configuration, and defect management. The role requires strong analytical and troubleshooting skills, effective stakeholder collaboration, and hands-on proficiency in Python to support testing activities and batch test automation.

Mandatory Skill(s)

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field;
• Must have experience in system testing and/or UAT testing;
• Must have proficiency in Python programming; 
• Strong analytical and problem-solving skills;
• Ability to work independently with minimal supervision and manage multiple tasks effectively;
• Proficiency in Microsoft Excel, Word, and PowerPoint.

Desirable Skill(s)

• Experience with FICO Blaze Advisor Rule Management System or Accelq automation testing tools;
• Familiarity with credit risk rules or banking workflow processes;
• Experience in UAT testing for Loan Origination Systems (LOS), including parameter setup and workflow validation.

Responsibilities

• Collaborate closely with internal stakeholders on Loan Origination System projects, focusing on system testing, credit rule configuration, and test pool preparation for unit testing;
• Support User Acceptance Testing (UAT) by addressing user and IT queries related to credit rule configuration;
• Configure and support the in-house batch testing tool for UAT;
• Apply Python programming to support testing and related activities;
• Work with IT teams and stakeholders to ensure timely delivery of projects;
• Manage and track UAT defects, ensuring timely resolution and effective communication with relevant parties.

If you are interested in this role, click on the “Apply to this job” button below or you could also write in with your CV to Sarah Sevilla at sarah.s@sciente.com quoting the job title.