Quantitative Developer

Responsibilities

• Writing and maintaining Python and R code that supports the investment research production processes
• Designing and creating software to enhance our data science technology stack
• Performing ad-hoc exploratory statistical analysis across multiple large complex data sets from a variety of structured and unstructured sources
• Implementing performance improvements in our data analysis and numerical programming code
• Running POCs to evaluate new technologies and libraries in the PyData ecosystem
• Staying up to date on the PyData ecosystem and evaluating new libraries and tools
• Working with software engineers to design feeds for new data sources from third-party vendors

Qualifications

• An undergraduate or graduate degree from an educational institution in computer science with a quantitative application such as mathematics and/or finance, or vice versa – a quantitative degree with a computer science application
• 1 - 3 years of relevant experience required
• Demonstrated professional or academic success
• Strong analytical, quantitative, and problem-solving skills
• Experience implementing production-grade Python code for a data analytic business, preferably in investment management
• Expert programming skills in Python with pandas and numpy
• Expertise in OOP paradigms, data structures, and numerical algorithms
• Understanding of probability and statistics, including linear regression and time-series analysis
• Curiosity and a willingness to learn new technologies
• Excellent communication skills, including data visualization
• A high energy and strong work ethic