Model Performance & Variable Analysis- C11- Manager

Candidate will be responsible for forecast performance analysis across model inventory, conceptualization of metrics to track performance at model and aggregated level, evaluation of different macro-economic and business drivers and corresponding impact on models. Candidate will also be involved in maintaining macroeconomic variables inventory across PPNR forecasting models, conducting reviews of different variables and expected linkages between different variable types, performing sensitivity testing and support model developers with required information on different macro drivers.

The candidate will evaluate innovative techniques to identify performance improving drivers in models to aid future iterations. Candidate will be required to analyze granular level data, identify patterns and outlier behavior across different balance sheet, income streams and drive stakeholder insights via thorough understanding of the data. Role would include conceptualization of quantitative and qualitative techniques, decision-based modeling approaches for incorporation of drivers with sparse data into models.

The candidate will be required to have a strong understanding of different macro-economic variables, and an ability to understand and interpret macro variable and index computations. Candidate should be able to understand interlinkages between variables and interpret economic scenarios in terms of possible impact on different variables. Key tasks would include identification and analysis of outliers in historical series and conducting comparative analysis across different scenarios to assess trends, anomalies and performing sensitivity analysis of macro drivers on model forecasts.

Candidate should possess relevant programming knowledge (such as Python, R, SAS or SQL) to automate data processes, generate summary reports and presentation of outcomes to senior Business/ Finance stakeholders supporting data-driven insights with impactful representation.


Required Skillsets

Bachelor’s/Master’s degree in economics/ statistics/ engineering, MBA or any degree with a focus on economics and analytics
Past experience on analyzing large datasets to relevant information and drive business insights
4-8 years of experience with experience on working in analytics with exposure to analyzing macro-economic variables
Good command over Python/ R/ SAS, SQL, excel, proficient in handling and analyzing large datasets from multiple source systems and alternate analytical/visualization tools
Detail oriented with good understanding of statistical models and forecasting techniques
Adequate understanding of finance, banking business and products and associated income streams.
Good presentation and interpretation skills
Ability to communicate and manage senior stakeholders across cross-functional teams
Ready to work within a collaborative environment with teams
Creative thinking for identifying new opportunities
-

Job Family Group:

Risk Management
-

Job Family:

Risk Analytics, Modeling, and Validation
-

Time Type:

-

Most Relevant Skills

Credible Challenge, Data Analysis, Laws and Regulations, Management Reporting, Policy and Procedure, Referral and Escalation, Risk Controls and Monitors, Risk Identification and Assessment, Risk Remediation.
-

Other Relevant Skills

Financial Planning and Analysis (FP&A), Model Governance, Model Transformations, Performance Modeling.
-

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, ****** orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.


If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View Citi’s EEO Policy Statement and the Know Your Rights poster.