Lead Assistant Manager

Job Description

We are seeking a skilled Data Engineer / Model Implementation Specialist with expertise in SAS and Python to join our team. The ideal candidate will have a strong background in the Credit Risk domain and will be responsible for designing, building, and implementing data models and pipelines to support credit risk modelling. Key Responsibilities Model Implementation: Implement and optimise credit risk models using SAS and Python to ensure accuracy and efficiency. Data Pipeline Development: Design, develop, and maintain data pipelines to support model implementation and data integration. Data Management: Manage and manipulate large datasets to support credit risk modelling and analysis. Collaboration: Work closely with data scientists, analysts, and other stakeholders to gather requirements and provide data solutions. Performance Optimisation: Optimise model performance and data processing to ensure timely and accurate reporting. Compliance: Ensure all data processes and models comply with regulatory standards and guidelines. Documentation: Maintain comprehensive documentation of data processes, models, and methodologies. Required Skills And Qualifications Technical Skills: Proficiency in SAS and Python is essential. Domain Knowledge: Strong understanding of the Credit Risk domain. Data Engineering: Experience in designing and building data pipelines and architectures. Model Implementation: Experience in implementing and optimising data models. Analytical Skills: Excellent analytical and problem-solving skills with the ability to perform complex data analysis. Attention to Detail: High level of accuracy and attention to detail in data processing and model implementation. Communication Skills: Strong verbal and written communication skills to effectively convey findings and recommendations. Experience: Previous experience in data engineering, model implementation, or a related field is preferred. Education Bachelor's degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees or certifications in Data Engineering or related areas are a plus. Show more Show less