4 дня назад
Risk Modeling Intern (Machine Learning)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Risk Modeling Intern (Machine Learning): Developing analytics, forecasting, and predictive models from structured and unstructured data to answer business questions and support decision-making with an accent on machine learning, traditional statistical modeling, and exploratory data analysis. Focus on implementing advanced models, working with large datasets, and explaining modeling methods to non-analytical users and model governance teams.
Location: Headquarters, Raleigh, North Carolina — hybrid schedule
Company
is a publicly traded U.S. private mortgage insurance provider offering borrower-centric products to lenders and other partners.
What you will do
- Design, create, and implement advanced analytics and forecasting models.
- Apply machine learning and traditional statistical modeling to support business decisions.
- Perform exploratory data analysis with large structured and unstructured datasets.
- Communicate models and analytical methods clearly to business users and model governance teams.
Requirements
- Be an undergraduate junior or first-year graduate student in a quantitative field such as statistics, econometrics, computer science, mathematics, data science, actuarial science, engineering, or a related discipline.
- Have experience applying machine learning algorithms to data.
- Have coding experience in Python, R, SAS, or a related language.
- Be able to communicate complex ideas to varied audiences.
- Have an interest in analyzing data in insurance, banking, or financial services.
- Have a minimum GPA of 3.2 on a 4.0 scale.
Nice to have
- Proficiency in Excel, Word, and PowerPoint.
- Exposure to insurance, banking, or financial services.
- Knowledge of cloud data services such as Snowflake or AWS.
- Experience with Structured Query Language.
Culture & Benefits
- Part-time, 12-week internship beginning May 17, 2027.
- Hands-on work on meaningful business projects alongside industry experts.
- Networking with company leaders, including the CEO.
- Team-building events, volunteer opportunities, and professional development workshops.
- Opportunities to develop a network of peers and mentors.
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