We are looking for Quantitative Developer Interns to join our Research team. We are a collaborative, data-driven, intellectually rigorous group responsible for proposing investment ideas, codifying these ideas into signals, and back-testing these signals in order to produce return, risk and trading cost forecasts to drive trading decisions. We work in a friendly environment and place a high value on learning, innovation, attitude and initiative.
Our Research Quantitative Development team is responsible for the tools, APIs, libraries and software development techniques to support faster generation, evaluation and productionization of investment ideas.
As a Quantitative Developer Intern, you will be immersed in our research efforts, working closely with Quant Researcher and Quant Developers to enhance our investment strategies. Our internship program combines theory and practice, providing real-world experience working in quantitative finance and technology. You will deliver high impact projects using technologies including cloud, distributed and high-performance compute, numeric computation, data visualization and APIs to solve complex problems in finance and research.
Responsibilities
Typical responsibilities include:
Solving complex quantitative problems with Python or R
Designing and developing tools or libraries to enhance our data science technology stack
Performing exploratory data analysis across large complex data sets to inform investment and signal ideas
Implementing performance improvements in our data analysis and numerical programming libraries
Running POCs to evaluate technologies and libraries in cloud and PyData ecosystems
Qualifications
Enrolled in an undergraduate or graduate program from an educational institution in a technical field, such as computer science or engineering, with an additional focus in data science, applied mathematics, economics. Expected degree completion within a year of the internship
Strong analytical, quantitative, programming and problems solving skills
Knowledge of software design paradigms, data structures, and numerical algorithms
Understanding of probability and statistics, including linear regression and time-series analysis
Excellent communication and collaboration skills
Interest in financial markets (prior experience not required)
Please include your transcript(s) upon submission of your application.
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.
