Quantitative Software Engineer

Quantitative Software Engineer - Build the Brain Behind Systematic TradingPrinceton, NJOwn the Platform That Powers Cutting-Edge Quantitative ResearchYou'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 OnYou'll sit inside a research group of scientists and engineers, building the backbone of their workflow:Quantitative research platform underpinning systematic trading strategiesMachine learning tools and frameworks for market and alternative dataResearch infrastructure for large-scale experimentsParallelized data transformation architecturesSystems for statistical analysis and reportingInfrastructure for handling complex market data structuresPython-based quantitative software librariesTools that integrate research, technology, and investment managementYou'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 DoingDesigning and implementing core components of the quantitative software platformMaintaining and extending novel machine learning tools for researchersBuilding and supporting research infrastructure for large-scale experimentsEnabling researchers to work efficiently with market and alternative data sourcesCollaborating closely with scientists, engineers, and investment professionalsWriting clean, elegant, well-structured Python and quantitative codeLeveraging probability, statistics, and machine learning in your designsUtilizing quantitative software libraries such as numpy/pandas and scikit-learnContributing to resilient, parallelized data transformation pipelinesCommunicating clearly in a complex, highly technical team environmentBringing intellectual curiosity to explore and implement new ideasUsing technology to solve challenging, research-driven problemsWhat We're Looking ForBachelor's or Master's degree in Computer Science, Engineering, or a closely related fieldExceptional programming proficiency, with a preference for PythonStrong software design skills and focus on code elegance and qualitySolid analytical foundation including probability, statistics, and machine learningHands-on experience with numpy/pandas, scikit-learn, or similar quantitative librariesAbility to communicate effectively in a complex, highly technical, collaborative environmentGenuine intellectual curiosity and passion for using technology to solve hard problemsComfort working at the intersection of research, technology, and investment managementThe Experience That Will Really Get Our AttentionYou'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 datasetsWhy 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 View email address on click.appcast.io McCarthy 484-238-1949KeywordsQuantitative Software Engineer, Quant Software Engineer, Quantitative Engineer, Python Engineer, Quant Developer, Quantitative Developer, Research Engineer, Machine Learning Engineer, Financial Engineering, systematic trading, market data, alternative data, equities datasets, futures datasets, FX datasets, probability, statistics, machine learning, numerical optimization, numpy, pandas, scikit-learn, quantitative libraries, data pipelines, parallelized data transformation, research infrastructure, trading systems, quantitative models, investment management, Princeton jobs