New Grad Full-Time Quantitative Researcher at WallStreetQuants

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Sep, 26

Salary

0.0

Posted On

29 Jun, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Quantitative Research, Statistical Modeling, Python, Machine Learning, Data Analysis, Probability, Linear Algebra, Optimization, Econometrics, Backtesting, Time-series Analysis, C++, R, SQL, Financial Modeling, Predictive Modeling

Industry

Education

Description

About the Role An NYC based hedge fund is seeking a highly motivated and intellectually curious New Grad Quantitative Researcher to join the team full time. This role is ideal for recent graduates who enjoy solving complex problems using mathematics, statistics, programming, and data-driven analysis. As a Quantitative Researcher, you will work at the intersection of financial markets, statistical modeling, and technology. You will collaborate with traders, developers, and other researchers to identify patterns in market data, develop predictive models, test trading hypotheses, and support the creation of quantitative strategies. This is an excellent opportunity for a new graduate who is analytical, creative, and excited to apply rigorous research methods to real-world financial markets. Responsibilities Conduct quantitative research to identify signals, patterns, and inefficiencies in financial markets. Analyze large and complex datasets, including market data, alternative data, and time-series data. Develop, test, and refine statistical models, predictive signals, and trading strategies. Design and run backtests, simulations, and experiments to evaluate research ideas. Collaborate with traders and developers to translate research findings into production-ready tools and strategies. Monitor model performance and contribute to ongoing strategy improvement. Apply techniques from statistics, machine learning, optimization, probability, and econometrics to solve trading-related problems. Present research findings clearly to technical and non-technical stakeholders. Stay current on market behavior, quantitative methods, and emerging research relevant to trading and investing. Qualifications Recent graduate or upcoming graduate from a Bachelor’s, Master’s, PhD, or equivalent program. Degree or strong demonstrated experience in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, Data Science, Operations Research, or a related discipline. Strong foundation in probability, statistics, linear algebra, optimization, or machine learning. Programming experience in Python, R, C++, Java, Julia, MATLAB, or a similar language. Experience working with data through coursework, research, internships, projects, or independent study. Strong analytical thinking, problem-solving ability, and attention to detail. Ability to communicate complex ideas clearly and work collaboratively across teams. Interest in financial markets, trading, investing, or data-driven decision-making. Preferred Qualifications Research, internship, or project experience involving statistical modeling, machine learning, time-series analysis, forecasting, optimization, or quantitative finance. Experience with Python data science libraries such as pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, or statsmodels. Familiarity with SQL, large-scale data processing, cloud tools, or distributed computing. Exposure to financial instruments such as equities, futures, options, fixed income, FX, commodities, or digital assets. Experience with backtesting, simulation, portfolio construction, or risk modeling. Participation in math competitions, programming competitions, research publications, Kaggle, hackathons, trading competitions, poker, chess, or other analytical competitions. What We Offer Full-time role designed for new graduates. Structured training and mentorship from experienced quantitative researchers, traders, and engineers. Opportunity to work on impactful research used in real-time trading and investment decisions. Exposure to financial markets, strategy development, data science, and trading infrastructure. A collaborative, intellectually rigorous environment where research quality and strong ideas are valued. Early ownership of meaningful research projects. Competitive compensation and benefits.

Responsibilities

Conduct quantitative research to identify market signals and develop predictive statistical models for trading strategies. Collaborate with traders and developers to translate research findings into production-ready tools and monitor model performance.