The role

SoFi’s Model Risk Management (MRM) team has responsibility for assuring that all quantitative models used at SoFi are conceptually sound and are appropriately used and monitored. A major activity in support of this objective is independent validations of all models, and ultimately approving models for use or requiring rework. Other activities include conducting reviews of periodic model performance monitoring reports, approving model changes, classifying models into risk tiers, and driving adoption of modeling best practices.
SoFi will soon possess a national bank charter from the Office of the Comptroller of the Currency. A strong Model Risk Management program is a key pre-requisite for operating a bank. As such, the Senior Analyst, Model Risk Management will perform highly visible and
important work and will touch virtually all functional areas within SoFi.

What you’ll do:

The Sr. Analyst, Model Risk Management will spend a majority of their time performing critical reviews of (or “validating”) quantitative models planned for use at SoFi. The analyst will read model documentation and engage in dialogue with model developers to understand how the model was built and how it functions. The analyst will assess the suitability of data used to build the model, the conceptual soundness of the modeling approach, and the appropriateness of the testing protocols and diagnostic metrics used on the model. The analyst will review results of diagnostic testing and analysis performed by the model owner and will conduct confirmatory or additional work as needed to have confidence in the model. The analyst will summarize their work and findings in a detailed written report, which will include formal recommendations and any required remediation work. 

The models to be validated will cover a range of statistical approaches from basic regression to cutting-edge machine learning algorithms. The models will also span multiple areas of the business, from credit risk scorecards to models used for optimizing back-office operational processes.

What you’ll need:
● Strong analytical skills with formal training in statistical analysis and demonstrated ability to drive business enhancements through data driven proposals

● Strong writing skills; ability to communicate technical concepts in understandable terms

● Proficiency in Python or R

● Self-starter who is comfortable working both alone and closely with teammates and business partners

● Minimum 5 years of related experience with a Bachelor’s degree in a quantitative discipline; or 3 years and a Master’s degree; or a PhD without experience; or equivalent experience

Nice to have:
● Prior model risk management experience in a banking environment

● Background in machine learning and artificial intelligence models