Risk Model Validation Associate - GenAI Machine Learning
Risk Model Validation Associate - GenAI Machine Learning
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Job Description
The Associate Risk Modeling conducts robust validations of a wide variety of risk models against established standards develops benchmarks and challenges and replicates models where applicable. Manages models of advanced complexity and leads special projects and/or programs.
Reviews and assesses overall model health within a given framework identifies potential problems and works with stakeholders to resolve.
Conducts robust validations of a wide variety of models against established standards develops benchmarks challenges and replicates models where applicable.
Assesses model performance and evaluates model assumptions and weaknesses.
Collaborates with model owners and develops to understand the business context for models.
Ensures adherence to the policies and procedures established by the company.
Qualifications: To perform this job successfully an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education: Bachelors Degree or equivalent work experience. Masters or equivalent degree in Statistics Mathematics Engineering Computer Science Economics or related fields is a preferred.
Work Experience: 5 years developing or validating quantitative machine learning (ML) models or Large Language Models (LLMs) frameworks. Experience in the financial services industry including expertise in risk modeling and regulatory compliance (SR 117 is preferred.
AI/ML Expertise: Demonstrated experience with Artificial Intelligence and Machine Learning (AI/ML) frameworks such as TensorFlow PyTorch and Scikitlearn. Handson experience with gradient boosting models NN and other ML algorithms for classification and regression.
LLM Knowledge: Experience with LLMs framework including models architecture methodology implementation APIs and evaluation with working knowledge of prompttuning and RAG/finetuning LLMs applications. Leaderboards review. Experience with Hugging Face models and datasets and testing design and for GenAI risks such as hallucination accuracy toxicity prompt injection bias etc.
Programming skills: Proficiency in Python and R. Experience in cloudbased solutions (AWS Azure) is a plus.
Excellent organizational skills strong communication with the ability to work crossfunctionally with model developers data engineers technology and governance teams.
EEO Statement:At Santander we value and respect differences in our workforce. We actively encourage everyone to apply.
Santander is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin genetics disability age veteran status or any other characteristic protected by law.
This job description does not list all of the job duties of the job. You may be asked by your supervisors or managers to perform other duties. You may be evaluated in part based upon your performance of the tasks listed in this job description. The employer has the right to revise this job description at any time. This job description is not a contract for employment and either you or the employer may terminate at any time for any reason.
The base pay range for this position is posted below and represents the annualized salary range. For hourly positions (nonexempt) the annual range is based on a 40hour work week. The exact compensation may vary based on skills experience training licensure and certifications and location.
Base Pay Range
Minimum:
Maximum:
Required Experience:
IC
Employment Type
Full-Time
