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The RUBY Model Onboarding team partners with Global Process Owners (GPOs) to standardize and design processes, ensuring alignment with standard data and technology platforms. This team serves as a central point of contact for strategic initiatives within Finance and Risk, providing a unified view of technology design, architecture, and prioritization. As a Senior Model Onboarding Specialist, Candidate will play a key role in supporting Citi's forecast processes by operating and managing RUBY (Forecast platform), a critical tool used for Interest Rate Risk, CCAR, and internal financial forecasting. Candidate will be involved in supporting both regulatory-mandated external forecast scenarios and internally focused planning and analytical exercises. This role involves a combination of executing existing forecast processes and collaborating with business and technology partners to identify and develop enhancements, improvements, and new functionality.
Job Responsibility:
Model Onboarding: Onboard new and revised models onto the RUBY platform, ensuring accuracy, efficiency, and adherence to established standards
Financial Analysis: Analyze Citi’s Financial statements like P&L and Balance Sheet for macro-economic or qualitative driver-based trends. Add qualitative inputs to Finance stakeholders number reviews using tools like Python, SQL
Collaboration: Partner with business and technology teams to identify and implement platform enhancements, improvements, and new features
Data Analysis: Analyze data inputs and outputs, ensuring data integrity, validity, and accuracy
Problem Solving: Troubleshoot and resolve issues related to model onboarding, data quality, and platform functionality
Communication: Communicate effectively with stakeholders, providing regular updates on project status and addressing any concerns
Risk Management: Identify and mitigate risks related to model onboarding and platform stability
Requirements:
5+ years of experience in financial services, with a focus on model development, validation, or implementation
Strong understanding of financial models, forecasting methodologies, and data structures
Good knowledge of Banking products, how financial institutions make money and impact of macro-economic conditions on the industry
Experience with SAS, Java, Python, or other modeling languages is a plus
Proficiency in SQL and data analysis techniques
Excellent communication, interpersonal, and problem-solving skills
Bachelor's degree in a quantitative field (e.g., Computer Science, Engineering, Finance). Master's degree preferred
Nice to have:
Experience with SAS, Java, Python, or other modeling languages
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