

The SVP Operational Risk Stress Testing manages the execution of stress tests for operational risk. These stress tests including enterprise stress tests, such as CCAR and DFAST and stress tests for entities across the globe where Citi has a presence. The role requires a balance of quantitative and analytics skills, leadership /management skills, and written and verbal communication skills. The quantitative and analytical skills are needed to understand the models, interpret results and contribute to the model development agenda. The SVP Operational Risk Stress Testing must work cross-functionally to manage the process and building consensus and support for recommendations. Below is more detail on the responsibilities:
Qualifications:
Education:
Anticipated Posting Close Date:
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Responsibilities:
Test Automation Strategy: Develop and implement a comprehensive test automation strategy for data pipelines, data warehouses, and data-driven applications.
Test Case Design: Design, develop, and maintain automated test cases to validate data quality, data integrity, and data transformations.
Test Script Development: Write and maintain robust and reusable test scripts using Python and relevant testing frameworks.
Data Validation: Develop automated data validation techniques to compare data sets, identify discrepancies, and ensure data accuracy.
Performance Testing: Design and execute performance tests to assess the scalability and performance of data pipelines and data processing systems.
Big Data Technologies: Utilize Apache Spark and Python to develop test automation solutions for big data environments.
CI/CD Integration: Integrate automated tests into the CI/CD pipeline to enable continuous testing and faster feedback loops.
Collaboration: Work closely with data engineers, data experts, and software developers to understand testing requirements and ensure test coverage.
Defect Management: Identify, track, and manage defects using a bug tracking system.
Reporting: Generate test reports and metrics to communicate test results and identify areas for improvement.
Continuous Improvement: Stay up-to-date with the latest trends and technologies in data testing and test automation and recommend best practices.
Qualifications/Experience:
6+ years experience in an IT Quality role. Ability to work independently or within groups on projects assigned
Minimum of 10 years of experience in Data test automation.
Proven experience in testing data pipelines, data warehouses, and data-intensive applications.
Strong proficiency in Python programming language.
Hands-on experience with Apache Spark and Big Data Ecosystem.
Experience with Enterprise test automation frameworks
Experience with CI/CD tools such as Jenkins, GitLab CI, or similar.
Experience with SQL and data validation techniques.
Education: Bachelor's degree in Computer Science, Engineering, or a related field.
Skills:
Strong understanding of data testing methodologies and best practices.
Excellent analytical and problem-solving skills.
Ability to work independently and as part of a team.
Excellent communication and interpersonal skills.
Anticipated Posting Close Date:

Duties: Perform a variety of object validation project requests and provide technical review of non-model objects developed with advanced machine learning and artificial intelligence methodologies. Perform the technical review process including the analysis and identification of an AI/ML object and distinguish such objects from a model. Perform research of the methodology and algorithm used for an object, while collecting the input and output of an object to assess the soundness of the object’s methodology. Scrutinize the performance testing results of the object and evaluate the potential risk exposed from the submitted object. Align the prescribed requirements of the Model Risk Management Review Policy for Non-model AI/ML objects, and comply with any additional requirements from U.S. regulators including FRB and OCC. A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite in accordance with Citi policies and protocols.
Requirements: Master’s degree, or foreign equivalent, in Applied Mathematics, Statistics (any), Actuarial Science, or a related field, and two (2) years of experience in the job offered or in a related quantitative occupation performing artificial intelligence (AI) and machine learning (ML) application review, validation, and risk analysis. Two (2) years of experience must include: Analyzing and assessing the risk of applications developed based on advanced Machine Learning (ML) techniques including natural language processing and generative AI; Utilizing statistical programming on R, Python, SAS, and VBA for independent and incremental testing of applications built with unsupervised learning methods, natural language processing, and generative AI; Developing generative AI and NLP model risk management guidelines and procedures to conduct model/object reviews including model/object identification, validation, and monitoring; Developing generative AI applications to compose validation reports with expertise in prompt engineering and evaluating the accuracy and efficiency of the generated reports; Fine-tuning generative AI to conduct specific banking related tasks, including sentiment analysis of customer credit card reviews and creating visualizations of cost-benefit analysis to guide the selection of base models; and Researching advanced evaluation methods for unsupervised learning applications and documenting feasibility analysis for future usage with case studies. Employer will accept pre- or post- Master’s degree experience. 40 hrs./wk. Applicants submit resumes at . Please reference Job ID# 25859781. EO Employer.
Wage Range: $144,700.00 to $175,300.00
Full timeIrving Texas United StatesPlease see the requirements listed above.For complementary skills, please see above and/or contact the recruiter.
Anticipated Posting Close Date:

By Joining Citi, you will become part of a global organisation whose mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress.
The role includes overseeing the obligations of the Senior Managers and Certification Regime (SMCR), which set standards of professional conduct for all individuals working in UK financial services, designed to enhance accountability and improve conduct within financial services firms and ensure that certain individuals in financial firms are competent and fit for their roles.
What you’ll do:
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By joining Citi London, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as:
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Requirements Gathering & Analysis:
Process Optimization:
Testing & Quality Assurance:
Training & Support:
Continuous Improvement:
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Certifications (Preferred but not required):
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Anticipated Posting Close Date:

Anticipated Posting Close Date:

Responsibilities:
Qualifications:
Education:
Anticipated Posting Close Date:

The SVP Operational Risk Stress Testing manages the execution of stress tests for operational risk. These stress tests including enterprise stress tests, such as CCAR and DFAST and stress tests for entities across the globe where Citi has a presence. The role requires a balance of quantitative and analytics skills, leadership /management skills, and written and verbal communication skills. The quantitative and analytical skills are needed to understand the models, interpret results and contribute to the model development agenda. The SVP Operational Risk Stress Testing must work cross-functionally to manage the process and building consensus and support for recommendations. Below is more detail on the responsibilities:
Qualifications:
Education:
Anticipated Posting Close Date:
משרות נוספות שיכולות לעניין אותך