Conduct quantitative research for high-frequency trading strategies across global markets. Responsibilities include processing data, generating signals, building statistical and machine learning models, simulating and calibrating strategies, and developing research pipelines and simulation environments. The role requires collaboration with experienced traders and researchers to deliver measurable trading performance and well-documented production-quality code.
Senior Quantitative Researcher opportunity with a high-frequency trading team focusing on developing alpha-driven trading strategies on the global markets using scientifically rigorous research and cutting-edge technology. This role will work closely with the team leader and other members on data processing, signal generation, modeling, strategy simulation and calibration, and developing the team’s research pipeline and simulation environments. This is a rare opportunity for an experienced researcher to join a well-positioned team at an early stage to deliver measurable and long-lasting PnL impact while collaborating with individuals with proven experience building some of the most profitable high-frequency strategies in the world.
Required Skills, Qualifications and Experience:
- Bachelors or advanced degree in a STEM major
- Strong intuition, hands-on mentality, and a keen interest in playing with data
- Knowledge of statistics, statistical modeling or machine learning techniques and knowing whether, when and how to apply them in data-driven research
- Programming skills in C++
- Programming skills in Python or other scripting languages
- Ideally 4+ years of working experience in quantitative trading, preferably in high-frequency trading
- Demonstrated ability to write well-documented code
- Passion for building research pipelines and tools
Similar Jobs
.png){kind=avatar}
Fintech • Machine Learning • Software • Financial Services
Conduct quantitative research for proprietary trading strategies by analyzing high-frequency market data, developing statistical and machine-learning models, building simulations and backtesting tools, and evaluating model performance. Collaborate with traders and developers to validate algorithms, improve pricing and execution, assess production readiness, prioritize research initiatives, and integrate validated models into low-latency trading systems. Mentor graduate researchers and interns.
Top Skills:
Algorithm DesignBacktestingDaskDerivatives PricingFinancial MathematicsHigh-Frequency TradingLightgbmLow-Latency Trading SystemsMachine LearningMarket MicrostructureMatplotlibNumbaNumerical OptimizationNumpyOptimizationPandasPolarsPortfolio ManagementPythonPyTorchRegression AnalysisRisk ModelingScikit-LearnScipySimulationStatistical InferenceStatistical LearningStatsmodelsTime-Series AnalysisXgboost
Financial Services
Develop and optimize quantitative trading strategies using large-scale financial datasets, statistical modeling, machine learning, and data analysis. Responsibilities span signal development, backtesting, production implementation, performance monitoring, and optimization. The role requires writing scalable code for live trading systems, diagnosing strategy behavior, collaborating with researchers, traders, and engineers, and continuously improving prediction and execution performance.
Top Skills:
CC++LinuxMachine LearningPythonUnix
Financial Services
Develop and refine electronic trading algorithms for equities, futures, FX, commodities, and indices. Conduct quantitative market research, backtesting, simulation, and real-time performance and risk monitoring. Build data pipelines and trading infrastructure using Python, Java, C++, KDB/q, and SQL. Optimize execution, manage trading risk, collaborate with technology, compliance, and controls teams, and communicate quantitative recommendations to technical and non-technical stakeholders.
Top Skills:
C++FixJavaJupyterKdb/QMatplotlibPlotlyPythonSQL
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
