Data Scientist - Fraud Modeling Analyst

As a Business Analytics Analyst in the Fraud Analytics team at Citi, you will play a crucial role in developing and validating fraud detection models to support Citis North American Cards business. Your responsibilities will include: - Partnering closely with Strategy partners and Model Risk Management validators to support the model lifecycle, including validation, ongoing performance evaluation, and annual reviews. - Conducting model development, validation, and testing for fraud detection models, utilizing statistical analysis, data validation, and model performance evaluation techniques. - Performing rigorous validation assessments for fraud model validation, developing and implementing validation methodologies to ensure model accuracy, robustness, and effectiveness. - Ensuring compliance with regulatory requirements and industry best practices in fraud detection and model validation. - Working with large and complex data sets to evaluate, recommend, and support the implementation of business strategies. - Identifying and compiling data sets using tools like Hive and SQL to help predict, improve, and measure the success of key business outcomes. - Documenting data requirements, data collection/processing/cleaning, and exploratory data analysis, potentially utilizing statistical models/algorithms and data visualization techniques. Qualifications required for this role include: - 3+ years of hands-on analytical experience - 2+ years of experience in statistical analysis with working knowledge of statistical software packages like Python (Must), Hive, Spark, SAS - Strong quantitative, analytical, and problem-solving skills, with knowledge of probability theory, statistics, mathematical finance, econometrics, and numerical methods - Understanding of statistical concepts, modeling techniques, and Model Implementation concepts, including traditional and advanced ML algorithms - Proficiency in statistical analysis and model validation techniques, with expertise in model evaluation techniques such as ROC curves, precision-recall, KS, cross-validation, feature importance, SHAP values, etc. - Familiarity with regulatory requirements and guidelines related to risk model validation - Strong communication and interpersonal skills, along with experience in Stakeholder management - Ability to work independently, with a risk and control mindset, and handle large volumes of transactional data Education required: - Masters/Bachelors degree in Statistics, Economics, Finance, Mathematics, or a related quantitative field; Engineering/MBA background from a premier institute If you are a person with a disability and need a reasonable accommodation to use Citis search tools and/or apply for a career opportunity, you can review Accessibility at Citi. Citi values diversity as a key business imperative and strives to foster a culture where the best people want to work, where individuals are promoted based on merit, and where opportunities for development are widely available to all.,