Purple Drive
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. Required Qualifications
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. Preferred Skills
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.
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. Required Qualifications
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. Preferred Skills
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.