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 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.

Key Responsibilities:

• 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.

Qualifications:

• 4+ years of experience in financial services, with a focus on model development, validation, or implementation.
• Good 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.

Competencies:

• Technical Proficiency:  Basic understanding of modeling tools, technologies, and data management principles.
• Analytical Skills:  Ability to analyze data sets and identify trends and patterns.
• Problem Solving:  Ability to identify and resolve technical and business problems.
• Communication:  Ability to communicate effectively with technical and non-technical audiences.
• Collaboration:  Ability to work effectively in a team environment.

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Job Family Group:

Technology

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Job Family:

Enterprise Architecture & Transformation

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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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