Vacancy expired!
Piper Companies is hiring a Credit Risk Modeling Senior Data Scientist. The primary purpose of this job is to develop and evaluate models associated with lending function to quantify the organization's credit risk exposure and evaluate the performance of established controls with minimal guidance from management. Incumbent provides statistical input for the development and implementation of policies, plans, and programs related to marketing, loan origination, portfolio management, loss forecasting and portfolio monitoring.
Responsibilities Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is not intended to be an all-inclusive list of job duties and the position will perform other duties as assigned. Interact with and advises Management regarding credit risk issues; formulates product strategy recommendations, and evaluates the risk in the overall loan portfolio. Aid in development of criteria for underwriting various product lines. Autonomous end-to-end statistical model creation, Including but not limited to identifying objectives, compiling data, sampling/prepping data, feature selection, model comparison/selection, deployment and monitoring. Ensures adequate internal control processes around model development, implementation and validation are established. Development, monitoring and maintenance of custom risk scorecards using advanced machine learning and statistical method. Recommends and implements model changes to improve performance of credit functions. Apply intermediate to advanced knowledge of financial processes and procedures, and routine modeling theories and techniques to create effective modeling solutions for a single or multiple business functions. Participate in corporate projects as requested. Keep informed of new ideas and academic research within the industry, best practices, and regulatory developments through publications, membership in professional organizations and contact with other financial institutions. Qualifications Equivalent combination of education and experience is considered. "- Development, monitoring and maintenance of custom risk scorecards using advanced machine learning and statistical method (e.g., logistic regression, decision tree, random forest, GBM etc.). - End-to-end statistical model creation, Including but not limited to identifying objectives, compiling data, sampling/prepping data, feature selection, model comparison/selection, deployment and monitoring. - Advanced programming skills to include knowledge of statistical programs (e.g. Python, SQL, SAS, and R). - Extensive knowledge/background in consumer banking products and credit risk modeling." Ph.D. or Master Degree with 2+ years' relevant working experience in a quantitative discipline is required. Applied experience with Logistic Regression, Linear Regression, Time Series Analysis, Decision Trees, Gradient Boosting Machine and other Machine Learning Methods. Advanced programming skills to include knowledge of statistical programs (e.g. SQL, SAS, SPSS, and R). Ability to manage multiple projects simultaneously and implement rapid changes in project direction. Proven project management skills. Excellent oral and written communication skills required. Supervisory Responsibility This position will not supervise employees.Vacancy expired!