Senior Model Onboarding Specialist VP

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.

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:

• 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 (, Computer Science, Engineering, Finance). Master's degree preferred.

Competencies:

• Technical Proficiency: Strong understanding of modeling tools, technologies, and data management principles.
• Analytical Skills: Ability to analyze complex 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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Primary Location Full Time Salary Range:

$111, - $161,

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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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Automated Processing and AI

We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

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