Quantitative Software Engineer - Build the brain behind systematic trading
Princeton, NJ
Own the platform that powers cutting-edge quantitative research
You ll be the engineer behind the models owning the quantitative software platform that drives large-scale scientific experiments on global markets.
This is where rigorous analysis meets robust engineering. You ll build and maintain novel machine learning tools and research infrastructure that our scientists and researchers rely on every day.
You re not just shipping features. You re enabling systematic trading strategies that run continuously across global markets.
If you love elegant Python, care deeply about infrastructure quality, and want your code to help crack hard scientific problems, this is your arena.
If that sounds like you, we want to talk.
What You'll Work On
You ll sit inside a research group of scientists and engineers, building the backbone of their workflow:
- Quantitative research platform underpinning systematic trading strategies
- Machine learning tools and frameworks for market and alternative data
- Research infrastructure for large-scale experiments
- Parallelized data transformation architectures
- Systems for statistical analysis and reporting
- Infrastructure for handling complex market data structures
- Python-based quantitative software libraries
- Tools that integrate research, technology, and investment management
You ll be working heavily with quantitative software libraries such as numpy, pandas, scikit-learn or equivalent packages.
Your code becomes the foundation that high-end quantitative research is built on.
What You'll Be Doing
- Designing and implementing core components of the quantitative software platform
- Maintaining and extending novel machine learning tools for researchers
- Building and supporting research infrastructure for large-scale experiments
- Enabling researchers to work efficiently with market and alternative data sources
- Collaborating closely with scientists, engineers, and investment professionals
- Writing clean, elegant, well-structured Python and quantitative code
- Leveraging probability, statistics, and machine learning in your designs
- Utilizing quantitative software libraries such as numpy/pandas and scikit-learn
- Contributing to resilient, parallelized data transformation pipelines
- Communicating clearly in a complex, highly technical team environment
- Bringing intellectual curiosity to explore and implement new ideas
- Using technology to solve challenging, research-driven problems
What We're Looking For
- Bachelor s or Master s degree in Computer Science, Engineering, or a closely related field
- Exceptional programming proficiency, with a preference for Python
- Strong software design skills and focus on code elegance and quality
- Solid analytical foundation including probability, statistics, and machine learning
- Hands-on experience with numpy/pandas, scikit-learn, or similar quantitative libraries
- Ability to communicate effectively in a complex, highly technical, collaborative environment
- Genuine intellectual curiosity and passion for using technology to solve hard problems
- Comfort working at the intersection of research, technology, and investment management
The Experience That Will Really Get Our Attention
You ve built serious research or data platforms before ideally where performance, resilience, and correctness really mattered. You know how to turn messy market-like data into something usable for machine learning, and you ve seen what happens when infrastructure isn t designed for scale.
You re fluent in Python s scientific stack, know your way around optimization and statistical tooling, and you re excited by the idea of working with equities, futures, or FX data structures in a highly collaborative research lab style environment.
High-signal technologies and concepts: Python numpy pandas scikit-learn machine learning probability statistics numerical optimization parallel data pipelines equities data futures data FX datasets
Why This Opportunity?
You ll join a research group where your engineering work directly impacts systematic trading strategies running across global markets.
You ll have high ownership and visibility within a close-knit team of experienced engineers and seasoned researchers, backed by extensive technical and data resources developed over decades of systematic trading.
In return, you ll receive competitive salary, bonus, and incentive compensation tied to overall firm performance, along with comprehensive, first-class benefits, catered lunch, an onsite gym, and the opportunity for qualified employees to invest alongside the firm.
You ll be part of a collaborative, intellectually rigorous environment with strong mentorship and long-term growth opportunities.
Interested?
If you re ready to own the platform that powers serious quantitative research and systematic trading, let s get you in the conversation.
Please send your resume to
Kevin McCarthy
Keywords
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