As a Quantitative Developer, your role involves contributing to the development of our upcoming Research data platform by utilizing open-source, cloud, and distributed computing technologies. You'll engage in impactful projects that rapidly gain adoption, instigating change within the team.
Key Responsibilities:
- Develop and maintain Python libraries supporting investment research production processes.
- Design and implement software to enhance our data science technology stack.
- Create financial data APIs and numerical APIs.
- Apply cloud and distributed computing technologies.
- Implement performance enhancements in data analysis and numerical programming code.
- Conduct Proof of Concepts (POCs) to assess new technologies and libraries in the PyData ecosystem.
- Collaborate with software engineers to design feeds for new data sources from third-party vendors.
- Propose and lead the implementation 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.
- Contribute to other projects based on experience and interest.
Qualifications:
- Bachelor's or Master's degree in computer science.
- Strong analytical and problem-solving skills.
- Proficient programming skills in Python, with experience in implementing production-grade Python code.
- Knowledge of OOP paradigms, data structures, and numerical algorithms.
- Familiarity with data storage (RDBMS, S3, columnar databases, NOSQL databases).
- Experience in distributed computing (Spark, Dask, or HPC).
- Understanding or 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 as well as a strong work ethic.
Additional 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.
