Top Quantitative Researcher Jobs in NYC, NY

As a Quantitative Researcher, you'll create and improve trading models while collaborating with senior researchers and conducting your own research.

Design, prototype, and productionize agentic LLM systems: frame problems, build datasets, develop models/agents, evaluate and monitor performance, and deploy robust, observable production code while partnering with cross-functional teams.

Quantitative Researchers will build models and strategies for pricing and trading financial instruments, collaborating closely with teams and using various techniques from statistical methods to deep learning.

Join BCBS as a quantitative researcher to support and manage systematic credit portfolios: validate data, develop signals and models, perform portfolio and risk analysis, optimize and hedge portfolios, build reporting/dashboards, and assist client- and product-related research and reporting.

Develop and test quantitative trading models using statistical and machine-learning methods on large financial datasets. Perform research-driven analysis, build predictive models, and communicate findings to integrate into strategy frameworks.

Quantitative Researchers develop predictive models, apply statistical methodologies to financial data, and design frameworks for risk and returns analysis.

As a Quantitative Researcher, you'll develop trading signals and models, implement research components, and evaluate them using statistical methods in a collaborative environment.

The role focuses on building tools for volatility research, designing trading strategies, analyzing data, and collaborating with a team to enhance trading strategies in volatility markets.

Develop and implement state-of-the-art machine learning models and statistical methods using massive structured and alternative datasets to discover predictive signals, design experiments, validate ideas through simulation, and collaborate to move research into production trading strategies.

The Quantitative Researcher will design, research, and deploy systematic trading strategies in global equity markets, conducting performance evaluation and managing risk.

As a Senior Quantitative Researcher, you will analyze large data sets, build statistical models, implement trading strategies, and develop quantitative research tools.

As a Quantitative Researcher, apply economic and statistical models to large-scale data, collaborating to solve quantitative challenges across industries.

Lead expansion into new opportunities by building and deploying profitable high-frequency quantitative trading strategies. Manage a research team to develop pricing and execution models, oversee end-to-end deployment, and integrate large-scale ML/Ops and high-performance compute into trading systems.

Conduct quantitative research for traders by testing market hypotheses, building and maintaining documented signals, performing event studies and backtests, and validating results against leakage, survivorship bias, transaction costs, and regime dependence. Organize reproducible point-in-time datasets, communicate findings clearly, track signal performance, and use AI tools to accelerate research and coding while verifying outputs.

Summer internship for graduate students to research and develop trading models from large datasets. Interns collaborate with senior quants and developers, complete one-to-two projects, receive training, and apply quantitative, mathematical, and programming skills (C/C++, Python, Pandas) to improve algorithmic trading strategies.

Undergraduate quant research intern to analyze financial datasets, clean and validate data, build simple models and backtests, write Python analysis and visualizations, and summarize results. Work collaboratively with researchers, traders, and engineers to develop and test systematic trading ideas.

Analyze execution data across equities, futures, and other asset classes to build and maintain market impact and trade-cost models. Develop tools and studies to improve execution, collaborate with traders, researchers, brokers, and operations, and present findings to senior researchers to reduce transaction costs and enhance portfolio performance.

Summer internship working with quantitative strategists to analyze large trading datasets, develop models to improve trading algorithms, complete one to two mentored projects, and participate in training and team events.

Develop and enhance data-driven trading strategies for US financial markets. Responsibilities include analyzing large datasets, generating predictive signals, collaborating with trading and engineering teams, and owning research and strategy development end to end. The role requires quantitative problem-solving, statistical analysis, programming, algorithms, and Linux/Unix expertise in a fast-paced research environment.

Develop sophisticated trading models using machine learning and data analysis. Manage the research process from data ingestion to model evaluation. Collaborate and contribute to all stages of financial model development leveraging deep learning.

The role involves conducting research to develop systematic macro strategies and signals focusing on market microstructure for trading. Responsibilities include feature engineering, modeling, backtesting, and improving trading environments.

Lead quantitative research, driving revenue and trading capabilities through collaboration with trading and technology, and applying rigorous scientific methods to solve business problems.

The Quantitative Researcher will analyze market data to build models and drive innovation in trading strategies, collaborating with traders and engineers.

The Quantitative Researcher will develop and optimize trading strategies, analyze data for alpha signals, and collaborate on financial models.

As a Quantitative Researcher, you'll develop trading algorithms, analyze financial data, create predictive models, and collaborate within a research team.