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Sr Analysts, Credit Risk Management is located in Bellevue, WA will analyze customer behavior to inform and refine credit strategies. Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week. No additional national or international travel is anticipated.
Job Responsibility
Forecast financial trends to support strategic decision-making
Evaluate and optimize the effectiveness of credit policies and outcomes
Develop customer risk segments to improve credit management and performance
Utilize statistical segmentation techniques to identify new opportunities
Performing complex qualitative and quantitative analysis of credit polices to ensure financial goals are being attained
Developing predictive financial and analytical models using the appropriate statistical methodologies, including trend and regression analysis
Participate and perform the analysis of new data and statistical products by external vendors
Performing loss forecasting analysis
Extracting, processing and transforming data from multiple disparate sources
Analyzing credit bureau data and alternative credit data
Requirements
Bachelor's degree in Computer Science, Computer Programming, Computer Engineering, Business Administration, or related, and 5 years of relevant work experience in any occupation in which the required experience is gained
Master's degree in Computer Science, Computer Programming, Computer Engineering, Business Administration, or related, and 3 years of experience in any occupation in which the required experience is gained
SQL, Excel VBA or analytical programming language R to manipulate and analyze large-scale datasets, derive critical insights, and translate complex findings into clear, actionable recommendations tailored for Executive Leadership
Snowflake, CV, CUW, or Teradata to extract, transform, and integrate data from multiple sources, with knowledge in managing the full Exploratory Data Analysis (EDA) lifecycle, including advanced querying, feature engineering, and building/managing data tables to ensure accuracy
Lead data-driven initiatives from requirements gathering to analytical framework design, with proficiency in leveraging statistical methods in R or Python including decision trees, regression models, and K-means clustering to enhance customer segmentation and credit risk strategies
Develop executive-level visualizations and performance tracking dashboards using Tableau, Power BI, SQL, Excel/VBA, and Python including pandas, matplotlib, and seaborn by performing ETL/data engineering including Extraction, Transformation, and Loading to deliver insights and monitor key metrics
Develop financial models and forecasts: Customer Lifetime Value prediction, cohort analysis, scenario modeling, using Excel, SQL, Python including NumPy, pandas, and scikit-learn to evaluate strategies and drive growth
Manage credit risk and underwriting by applying knowledge of credit structures and leveraging transactional, payment, and consumer behavioral data to build predictive models and develop optimization models in Excel and Python to design and implement new credit initiatives