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Job description
Job Title: Senior Quantitative Software Engineer
Location: Chicago, IL (Onsite - Local Candidates Preferred)
Type: Contract
Job Description
We are seeking a Senior Quantitative Software Engineer with strong expertise in software engineering, quantitative research, and financial analytics. The ideal candidate will combine advanced programming skills with deep knowledge of quantitative modeling to support quant research, equity portfolio management, and risk analytics. This role requires hands-on technical leadership, collaboration with quantitative researchers, and the ability to design and deliver scalable, high-quality solutions for a front-office environment.
Key Responsibilities
- Collaborate with business product owners and quantitative teams to design and deliver technology platforms and solutions for Quant Research.
- Develop code libraries, tools, and applications to support research-driven investment and analytics processes.
- Lead and mentor developers to identify and productionize mature prototypes.
- Design large-scale distributed computing solutions for quantitative analytics and create user-friendly visualizations.
- Implement standards, processes, and tools for numerical library testing, code quality, and review.
- Evaluate methods, datasets, and tools to deliver optimal quantitative and technical solutions.
- Partner with Quants to implement models for investment decision-making.
- Innovate and improve proprietary models and algorithms with focus on scalability, resiliency, and performance.
- Conduct code reviews with peers and provide feedback to ensure high-quality deliverables.
- 12+ years of progressive experience in software engineering and quantitative analysis.
- Advanced degree in Computer Science, Math, or Financial Engineering.
- Strong experience in Python and PySpark (must-have), with additional proficiency in R, Java, and distributed computing frameworks.
- Expertise with big data & cloud computation platforms (e.g., Databricks, AWS, Azure).
- Hands-on experience with PySpark, Pandas, Polars, Cuml for large-scale data analysis.
- Strong knowledge of statistics, time-series analysis, algorithms, asset pricing theory.
- Experience building and supporting real-time, batch, and orchestrated architectures.
- Strong Test-Driven Development mindset.
- Solid understanding of financial instruments (securities, derivatives) and capital markets.
- Strong communication skills with ability to explain complex concepts to non-technical stakeholders.
- Prior front-office software development experience in Asset Management, Hedge Funds, or Investment Banking.
- Experience building containerized applications and deploying on cloud platforms (Azure, AWS).
- Exposure to web-based visualization technologies for large/complex datasets.
Note: This is an onsite contract role in Chicago, IL - local candidates are strongly preferred.
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Quantitative Software Engineer?
A: To succeed as a Quantitative Software Engineer, key technical skills include proficiency in programming languages such as Python, C++, or Java, as well as expertise in data structures, algorithms, and software design patterns. Additionally, strong mathematical and statistical knowledge, particularly in linear algebra, calculus, and probability, is essential for working with complex data and modeling systems. Soft skills like effective communication, problem-solving, and collaboration are also crucial, as Quantitative Software Engineers often work in cross-functional teams and must convey technical insights to non-technical stakeholders.\n\nThese technical and soft skills enable Quantitative Software Engineers to design, develop, and deploy high-quality software solutions that drive business value and drive career growth through opportunities in leadership, technical specialization, or entrepreneurship.
Q: What is the career path for a Quantitative Software Engineer?
A: A Quantitative Software Engineer's career path typically begins with entry-level roles such as Quantitative Software Developer or Junior Quantitative Analyst, where they focus on developing and implementing mathematical models and algorithms in software applications. As they gain experience, they progress to mid-level roles like Quantitative Software Engineer or Senior Quantitative Analyst, where they lead projects, mentor junior team members, and contribute to the development of complex software systems. Ultimately, senior roles such as Technical Lead, Quantitative Software Architect, or even Director of Quantitative Engineering may be achieved, offering opportunities for strategic leadership, innovation, and career advancement in fields like finance, data science, or technology.