Associate – Quantitative Developer

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
Demonstrated professional or academic success (recent graduates are encouraged to apply)
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
Interest in financial markets (prior experience not required)
Excellent communication skills, including data visualization
High energy and strong work ethic

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

Some experience programming in R with tidyverse packages
High-performance computing
Distributed computing
Hadoop, Spark, Kafka, and related technologies
SQL
Unix/Linux system tools and environment
Basic familiarity with unit testing, continuous integration, DevOps, containerization
Interactive data visualization and dashboards