What are the responsibilities and job description for the Quantitative Analyst position at Santander Holdings USA Inc?
Job Overview
Santander Holdings USA Inc is seeking a highly skilled Quantitative Analyst to join its team. As an Associate in Data Science focusing on Credit and Lending Modeling, you will develop and implement advanced predictive models that enhance lending decisions while minimizing risk.
About the Role
You will be responsible for building analytical data pipelines, applying machine learning methodologies, and ensuring model compliance and performance to support strategic business growth. You will also collaborate with cross-functional teams to communicate insights and findings effectively, contributing to overall financial stability.
Requirements
To be successful in this role, you should have:
Santander Holdings USA Inc is seeking a highly skilled Quantitative Analyst to join its team. As an Associate in Data Science focusing on Credit and Lending Modeling, you will develop and implement advanced predictive models that enhance lending decisions while minimizing risk.
About the Role
You will be responsible for building analytical data pipelines, applying machine learning methodologies, and ensuring model compliance and performance to support strategic business growth. You will also collaborate with cross-functional teams to communicate insights and findings effectively, contributing to overall financial stability.
- Create, implement, and validate machine learning models including rigorous documentation of code and results.
- Investigate, define, and iterate with business partners to define business problems and data science use cases.
- Communicate in person, via email, and in virtual meetings with internal and external team members on updates & status.
- Mine and manipulate data from disparate systems and environments.
- Use statistics to analyze data and produce insights on tight timelines.
Requirements
To be successful in this role, you should have:
- 3 years' experience in a data science or quantitative role working hands-on with code to build predictive models and advanced analytics applied to large-scale data-intensive projects.
- Strong knowledge of credit risk concepts, including PD, LGD, EAD, Stress testing and scorecard development.
- Awareness of model bias and how to mitigate it.
- Honed application of the research process – exploration, hypothesis creation, and iteration.
- Deep understanding of statistics or advanced mathematics like Bayesian inference, optimization, linear algebra.
- Ability to explain failures as well as successes as you build understanding in an emerging area.
- Confidence with cloud computing in AWS or GCP.
- Advanced in at least one machine learning programming language and framework (Python, R, etc.).
- Experience using data science methodologies including regression/classification, XgBoost, time-series modeling, and algorithm/network optimization.
