Top Quantitative Researcher Jobs in NYC, NY

Conduct quantitative research for investment strategies using advanced statistical and mathematical modeling, machine learning, data analysis, portfolio optimization, and algorithm development. Build predictive models and analyze price formation, risk, and financial market drivers. Collaborate with researchers, engineers, and traders to develop scalable systems and solve real-world investment problems.

Develop and improve mathematical models and trading approaches. Conduct statistical analysis and back test trading strategies in a fast-paced environment.

Conduct quantitative research for financial markets by developing valuation strategies, mathematical models, trading signals, and monetization systems. Responsibilities include translating algorithms into code, backtesting and implementing trading models, analyzing unconventional data sources, and applying statistical techniques. The 11-week post-doctoral internship involves collaboration with senior researchers in a fast-paced investment environment.

Develop and deploy advanced statistical and ML models on large-scale alternative datasets to generate investable signals, partner with investment teams, evaluate data quality, and drive novel data-driven research with commercial impact.

Develop and enhance quantitative models for collateral risk and lending value estimation. Conduct empirical research on market, liquidity, volatility, concentration, and idiosyncratic risks; establish performance benchmarks; curate and reconcile data; and provide insights supporting lending and product strategy. Partner with investment solutions, credit, risk, lending, technology, and model risk teams while communicating methodologies and findings to senior management and regulators.

Lead end-to-end quantitative market research, including research planning, surveys, advanced statistical analysis, synthesis, and stakeholder presentations. Build and manage brand and sentiment measurement programs, identify customer and market trends, and provide strategic recommendations for growth and product opportunities. Partner with business leaders, promote research-driven decision-making, and mentor junior researchers while scaling the organization’s research practice.

Conduct innovative machine learning research and develop scalable, robust models for financial markets across asset classes. Apply deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, fine-tuning, and reinforcement learning to model price formation, market behavior, and risk. Design, implement, optimize, and deploy models using Python and modern machine learning frameworks while collaborating with quantitative researchers, engineers, and traders.

Conduct quantitative research for automated trading strategies by developing mathematical models, translating algorithms into code, backtesting trading signals, analyzing unconventional data, and refining monetization systems. Collaborate with senior researchers during an 11-week post-doctoral internship while applying advanced probability, statistics, machine learning, and time-series techniques to financial markets.

Conduct quantitative research for a global, mid-frequency statistical arbitrage portfolio. Responsibilities include exploring alternative datasets, developing trading signals, improving portfolio construction, risk and transaction cost models, applying machine learning and data science techniques, writing production-quality code, and managing research projects from idea generation through implementation.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Designs and manages Qualtrics in-product intercept surveys, targeting workflows, directories, and data collection. Analyzes user behavior, product performance, and survey feedback; builds dashboards and communicates actionable insights to product, UX, and leadership teams. Collaborates with qualitative researchers, data engineering, and development teams to integrate survey data with behavioral analytics platforms and enable access to behavioral datasets across B2B and B2C products.

Conduct applied quantitative research in global financial markets by analyzing large-scale market and order-flow data, developing predictive, statistical, stochastic, and machine learning models, testing hypotheses, and identifying trading opportunities. Researchers validate models in live market environments and collaborate with engineers and traders. The role includes structured graduate onboarding and requires a PhD in a quantitative STEM field, expected completion by mid-2027.

Conduct quantitative research to identify trading opportunities and develop trading strategies. Analyze financial datasets using statistical and probabilistic methods, distinguish signal from noise, and investigate market dynamics and microstructure. Build and use research frameworks, apply coding skills in languages such as C++ and Python, and collaborate across projects to improve the firm’s trading capabilities and profitability.

Designs and implements pricing and risk infrastructure for Polymarket’s perpetual futures exchange. Responsibilities include aggregating spot prices, creating funding-rate formulas, setting margin and leverage parameters, writing formal specifications, shipping production code, and monitoring live-market performance. The role investigates pricing anomalies, handles market-data failures and adversarial conditions, and owns continuous improvements to production systems.

As a PhD intern, you will develop and test trading strategies, perform statistical analysis, and collaborate with senior researchers.

Conduct research and develop automated trading strategies using advanced statistical techniques and programming skills. Collaborate in a fast-paced team to innovate and implement quantitative models.

Lead quantitative UX research across R&D, shaping high-stakes product investments and AI experience decisions. Develop psychometric frameworks, surveys, segmentation, usability benchmarks, pricing research, and statistical models. Partner with Data Science to integrate behavioral and attitudinal data, establish scalable research standards, mentor researchers, and enable non-researchers to conduct rigorous studies. The role requires executive-level influence, expertise in AI-powered products, and hands-on proficiency with SQL, Python, and Qualtrics.

Develop and maintain portfolio construction factor models, research statistical market patterns, create valuation strategies, and backtest financial signals for live trading. The role applies machine learning, statistics, and quantitative finance to investment products while collaborating with investment leadership, Product, Engineering, Compliance, and Legal on launches, methodology improvements, and policies.

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.

Conduct research, statistical analyses, and develop automated trading strategies using large data sets and sophisticated statistical techniques.

Researches and develops equity execution models, transaction cost models, order-routing strategies, and analytical tools. Applies statistical, mathematical, computational, and machine learning techniques to forecasting, sentiment analysis, execution optimization, performance measurement, and risk attribution. Collaborates with electronic trading, development, technology, and model validation teams to assess, document, maintain, and deploy commercially viable trading algorithms.

Conduct quantitative research for high-frequency trading and prediction-market strategies. Analyze order book, trade, sports, and prediction-market data; develop statistically significant signals, pricing models, liquidity-management techniques, and latency-sensitive strategies. Interns may rotate across trading tracks and participate in coding tests and quantitative interviews. The role requires advanced statistical research, Python, C++, market microstructure knowledge, and machine-learning experience.

As a Quantitative Researcher, you will analyze data, develop alpha signals, collaborate on performance analysis, and create pricing models while assessing risk.

Design, build, optimize, and deploy systematic trading models and algorithms. Analyze large datasets to identify market patterns and trading signals, collaborate with traders and technologists to productionize research, and monitor and refine models based on live performance. The role requires advanced quantitative expertise, strong programming skills in Python or C++, and the ability to solve open-ended problems independently.

Quantitative Researchers at Aquatic create and improve trading models using data and statistical methods, collaborating with engineers and leaders.