AVP Data Scientist-Fraud Model Development

As a Specialized Analytics Senior Analyst at the company, you will be a seasoned professional contributing to the development of new techniques and the improvement of processes in the area. Your role will integrate subject matter and industry expertise within a defined area, requiring an in-depth understanding of how areas collectively integrate within the sub-function to contribute to the objectives of the function and overall business. **Key Responsibilities:** - Partner closely with Strategy partners and Model Risk Management validators across the model lifecycle, including validation, ongoing performance evaluation, and annual reviews. - Develop, validate, and test fraud detection models, including statistical analysis, data validation, and model performance evaluation. - Conduct rigorous validation assessment for fraud model validation, ensuring compliance with regulatory requirements and industry best practices. - Work with large and complex data sets to evaluate, recommend, and support the implementation of advanced Machine Learning Models. - Identify and compile data sets using tools like Hive and SQL to predict, improve, and measure the success of key business outcomes. - Document data requirements, data collection/processing/cleaning, and exploratory data analysis utilizing statistical models/algorithms and data visualization techniques. - Specialize in fraud or risk domain, appropriately assessing risk when making business decisions. **Qualifications:** - 8+ years of hands-on analytical experience - 5+ years of experience in statistical analysis with proficiency in Python (Must), Hive, Spark, SAS - Strong quantitative, analytical, and problem-solving skills with knowledge of probability theory, statistics, mathematical finance, econometrics, and numerical methods. - Proficiency in statistical analysis and model validation techniques, traditional and advanced modeling techniques, and algorithms. - Expertise in model evaluation techniques such as ROC curves, precision-recall, KS, cross-validation, feature importance, SHAP values, etc. - Familiarity with regulatory requirements related to risk model validation. - Strong communication, interpersonal, project management, organizational, and stakeholder management skills. - Ability to work independently, handle large volumes of transactional data, and deliver projects in a fast-paced environment. **Education:** - Masters/Bachelors/PhD degree in Statistics, Economics, Finance, Mathematics, or a related quantitative field; Engineering/MBA background from a premier institute. This job description provides a high-level overview of the work performed in the Decision Management job family group, specifically in the Specialized Analytics (Data Science/Computational Statistics) job family.,