Title: Senior Quantitative Developer Location: Chicago, IL-Onsite MUST HAVE: • An advanced Computer Science, Math or Financial Engineering degree from a reputed institution. • 12+ years of progressive experience in software engineering and quantitative analysis. • 7+ years of experience in Quantitative Research & Analysis. • Experience working with and analyzing large data sets, and using necessary libraries like PySpark, Pandas, Polars, Cuml, etc. • Expert knowledge in multiple programming language(s) - Python, PySpark, R, Java etc. Python / PySpark is must have expertise • Working knowledge of one or more relevant big data cloud computation platform like Databricks • Experience with algorithms and data structures. Responsibilities • Collaborate with business product owners and quantitative teams to understand help drive technology platform and solutions to meet quantitative and analytics needs for Quant Research business • Work on the development of code libraries and solutions that leverage and appropriately augment existing structures to meet the needs of the research-driven investment and analysis processes, often in the absence of clearly documented specifications. • Lead and work with developers to identify which interim solutions (e.g., tools, applications, reports, data structures, etc.) have matured sufficiently to transition to a production environment, and produce specifications for such solutions, enabling IT to elevate strategically targeted prototypes to production. • Identify and evaluate the most appropriate methods, tools, datasets and technology solutions to address requirements. • Partnering with Product owners and Quants to help implement models to inform the investment decision making process • Building large scale distributed computing programs to generate insightful analytics and present results in user-friendly visualization • Implement standards, processes, and tools for numerical library testing and code quality controls • Review implementation of complex models and algorithms focusing on requirement verification and code quality. Conduct code review with peers and model developers and obtain their feedback. • Innovate and improve proprietary models and algorithms; design and deliver in terms of high reliability, resiliency and scalability