Role Summary
We are looking for an experienced Quant Developer with Python experience , to join our Research group. We are a collaborative, data-driven, intellectually rigorous team responsible for coming up with investment ideas, codifying those ideas into signals, back-testing the signals, and producing return, risk and trading cost forecasts based on the signals to drive trading decisions. We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.
Our development team within Research is responsible for the tools, APIs, libraries and software engineering techniques to support faster generation, evaluation and productionization of investment ideas.
As a Quantitative Developer, you will help build our next-generation Research data platform leveraging open-source, cloud and distributed computing technologies. You will work on high-impact projects that are quickly adopted and drive change across the team.
Responsibilities:
Writing and maintaining Python libraries that supports the investment research production processes
Designing and creating software to enhance our data science technology stack
Design and implement financial data APIs and numerical APIs
Apply cloud and distributed computing technologies
Implementing performance improvements in our data analysis and numerical programming code
Running POCs to evaluate new technologies and libraries in the PyData ecosystem
Working with software engineers to design feeds for new data sources from third-party vendors
Propose and lead implementations of major components or features in our data science platform
Mentor, train and provide technical guidance to junior team members in design and coding standards
Other projects based on experience and interest.
Qualifications:
An undergraduate or graduate degree from an educational institution in computer science
Strong analytical and problem solving skills
Expert programming skills in Python, experience implementing production-grade Python code
Experience in OOP paradigms, data structures, and numerical algorithms
Data storage: RDBMS, S3, columnar databases, NOSQL databases
Distributed computing: Spark, Dask, or HPC
Understanding/interest in probability and statistics, including linear regression and time-series analysis
Curiosity and a willingness to learn new technologies
Interest in financial markets (prior experience not required)
Excellent communication skills
High energy and strong work ethic
In addition, experience with any of the following would be valuable:
Hadoop, Spark, Kafka, and related technologies
Unix/Linux system tools and environment
Basic familiarity with unit testing, continuous integration, DevOps, containerization
Interactive data visualization and dashboards
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.