Quantitative Summer Institute is a 12-week summer internship program targeted at hard-working and self-motivated students with curiosity about finance, mathematics, data analysis, programming, and technology.
Spend your internship working alongside our top tier professionals in Quantitative Analysis and Technology (QAT) group. Gain training opportunity and valuable hands-on experience in the areas of quantitative finance, market risk, econometric modelling, data analysis and governance, quant technology and infrastructure delivery.
The QSI program is a combination of classroom sessions and project assignments. The QSI training modules are an in-house training program led by the Quantitative Analysis and Technology Group. These sessions, accompanied by practical assignments, give real world experience by using the same tools as those used by our modelers, traders, structurers, data analysts and software developers.
Throughout the application process, you will have an opportunity to learn about the QAT diverse group hiring through the Summer QSI program. Interns will be placed in a role based on their background and interests. Some of these opportunities include:
Quantitative Strategies: we develop and maintain quantitative models, analytics and pricing tools for financial instruments and risk reporting. With our modelling expertise, we support all areas of the bank, our main customers are Trading and Risk Managers, covering all the key asset classes within the firm. Technologies used: F#/C#/Python/C++/TeamCity.
Projections Modelling: we develop and maintain projection models based on time series data, which are used in stress-testing to construct multi-quarter macroeconomic scenarios as well as project the bank’s revenue, exposures, and Value-at-Risk.
Quant Engineering: we are a group of software engineers and quant developers delivering applications, services and libraries for derivatives pricing. Technologies used: C#/F#/React/OpenShift/TeamCity/Jenkins/Docker/Splunk.
Quant Technology: we are a group of software engineers working on the development platform, test frameworks/tools, CI/CD infrastructure and core elements of Credit Suisse primary modelling library. Technologies used: C#/React/F#/C++/TeamCity/SxS.
Data Strategy and Governance: we analyse data, apply knowledge of market risk and market data to solve data quality issues, implement data governance framework and controls around the data.
You will be in your pre-final year of graduate degree program, studying to acquire a degree in a quantitative field such as mathematics, econometrics, statistics, data science, finance, or computer science
Availability for a period July-September 2023
Solid knowledge in one of below fields:
--> Mathematics and programming (least one major programming language C++/ C#/Java /F#/Python)
--> Time-series analysis techniques, and more general econometric modeling methods (ARDL, ECM, ARIMA, VAR, GLM) and their application on R language
Data analysis, financial instruments and risk concepts
Software development practices – automated tests, continuous integration, agile methodologies
Good presentation skills, ability to document and communicate complex topics to a diverse range of audiences
Proficient written and spoken English
Dedication to fostering an inclusive culture and value diverse perspectives