Fraud Modeling Analyst

The Spec Analytics Analyst is a developing professional role. Applies specialty area knowledge in monitoring, assessing, analyzing and/or evaluating processes and data. Identifies policy gaps and formulates policies. Interprets data and makes recommendations. Researches and interprets factual information. Identifies inconsistencies in data or results, defines business issues and formulates recommendations on policies, procedures or practices. Integrates established disciplinary knowledge within own specialty area with basic understanding of related industry practices. Good understanding of how the team interacts with others in accomplishing the objectives of the area. Develops working knowledge of industry practices and standards. Limited but direct impact on the business through the quality of the tasks/services provided. Impact of the job holder is restricted to own team.
Responsibilities:
Partner closely with Strategy partners and Model Risk Management validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews.
Responsible for model development, validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation.
Conduct rigorous validation assessment for fraud model validation; develop and implement validation methodologies to assess model accuracy, robustness, and effectiveness.
Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation.
Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies.
Identifies and compiles data sets using a variety of tools (e.g. Hive, SQL) to help predict, improve, and measure the success of key business to business outcomes
Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include utilizing statistical models / algorithms and data visualization technique.
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
Qualifications:
3+ years of hands-on analytical experience
2+ years’ experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SAS
Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods
Strong understanding of statistical concepts and modelling techniques including traditional and advanced ML algorithms
Strong proficiency in statistical analysis and model validation techniques. A solid grasp of traditional and advanced modeling techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc.
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; experience with Stakeholder management
Ability to work independently. Risk and control mindset: ability to ask incisive questions, assess materiality and escalate issues.
Ability to handle large volumes of transactional data. Familiarity with data extraction tools like Hive will be an advantage.
Successful candidate will have a demonstrable analytical problem solving, and the ability to deliver projects in a fast-paced environment. Willing to learn and can-do attitude.
Education:
Master’s/Bachelor’s 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 review of the types of work performed. Other job-related duties may be assigned as required.
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Job Family Group: Decision Management
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Job Family:Specialized Analytics (Data Science/Computational Statistics)
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Time Type:Full time
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Most Relevant Skills Please see the requirements listed above.
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Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.
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