About:

• Location: Chicago, IL
• Contract: 6+ months

The Role:

• 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

Tech, business and leadership skills:

• Strong domain skills – Quantitative Research, Risk, Equity Portfolio Management etc.
• Works in many technologies and adapts fast to new technologies
• Adept with various architectures including real-time, batch, orchestration
• Adept with multiple parts of the software lifecycle (e.g., coding, testing, development)
• Stays abreast of industry trends and technologies and knows when/how/if to apply them appropriately
• Conversant with providing a clear explanation of strategy, technical concepts, designs or implementation to a non-technical audience

Qualifications

• An advanced Computer Science, Math or Financial Engineering degree from a reputed institution.
• 12+ years of progressive experience in software engineering and quantitative analysis.
• Willingness and excitement to learn unfamiliar quantitative subjects or tools/technologies, as required on the job.
• Strong analytical skills; experience working with and analyzing large data sets, and using necessary libraries like PySpark, Pandas, Polars, Cuml, etc.
• Proficiency in coding, demonstrated interest in translating algorithms and models into production quality?code
• 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
• Strong Test-Driven Development and desire to write simple, adaptive and iterative code
• A solid understanding of tradable financial instruments (securities, derivatives) and capital markets
• An advanced level of relevant mathematical knowledge e.g. statistics, time-series analysis, asset pricing theory, algorithms
• Experience with algorithms and data structures