You will:
Manage a team that will design, develop, and implement predictive models, Machine Learning algorithms, and statistical techniques to assess fair lending risks and detect potential instances of discrimination
Analyze large datasets and identify patterns, trends, and potential areas of concern related to Fair Lending practices
Utilize advanced statistical methods to evaluate model performance, including model calibration, validation, and interpretation of results
Collaborate with cross-functional teams to understand business requirements and develop data -driven solutions for Fair Lending compliance
Develop and maintain of scalable data pipelines, data models, and analytical tools to support fair lending analysis and reporting activities
You have:
5+ years of experience in data analysis, statistical modeling, and predictive analytics within the financial services industry, preferably in Fair Lending or credit decisioning – Must
Bachelor's degree in Statistics, Mathematics, data Science, Economics, or a quantitative field. – Must (Advance degree an advantage)
Proficient in Hebrew and English both written and verbal, sufficient for achieving consensus and success in a remote and largely asynchronous work environment – Must
Strong knowledge of advanced analytics and Machine Learning techniques such as regression and classification algorithms, including linear and logistic regression, k-nearest neighbors, support vector machines (SVMs) and other techniques
Experience working with cloud-based data platforms and technologies such as AWS and Sagemaker for scalable data analytics and Machine Learning
