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Internship Mathematical Optimization Jobs in New York

... an internship: Anomaly detection using deep neural networks Numerical optimization applied to ... Mathematics Natural or Social Sciences Relevant additional backgrounds also considered Essential ...

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Internship Mathematical Optimization information

What is an internship in mathematical optimization?

An Internship in Mathematical Optimization is a temporary position for students or recent graduates to gain practical experience applying mathematical techniques to solve optimization problems. These internships typically involve tasks such as modeling real-world scenarios, developing algorithms, and using software tools to find optimal solutions in areas like logistics, finance, or engineering. Interns often work with experienced professionals, contributing to research projects or business applications while building their technical skills. The role usually requires a solid foundation in mathematics, programming, and analytical thinking.

What types of projects can I expect to work on during an internship in mathematical optimization?

As an intern in Mathematical Optimization, you will typically work on real-world problems that involve designing, implementing, and testing optimization algorithms. Projects may include tasks such as modeling supply chain logistics, scheduling operations, or improving resource allocation for various industries. You'll likely collaborate with data scientists, engineers, and other interns to collect data, build models, and present findings. This hands-on experience helps you develop both technical and teamwork skills, and often includes mentorship from senior optimization experts.

What are the key skills and qualifications needed to thrive in an internship in mathematical optimization?

To thrive in an Internship in Mathematical Optimization, you need a solid background in mathematics, particularly in optimization theory, linear algebra, and programming, usually supported by ongoing or completed studies in applied mathematics, engineering, or a related field. Familiarity with optimization software (like Gurobi or CPLEX), programming languages such as Python or MATLAB, and experience with relevant libraries or frameworks is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help interns stand out when solving complex problems and collaborating with teams. These skills are crucial for developing efficient optimization solutions and contributing meaningfully to research or industry projects.

What is the difference between Internship Mathematical Optimization vs Data Analyst Intern?

AspectInternship Mathematical OptimizationData Analyst Intern
Required CredentialsBasic knowledge of optimization, programming skillsStatistics, data analysis, programming
Work EnvironmentResearch, algorithm development, modelingData collection, reporting, visualization
Industry UsageOperations research, logistics, supply chainBusiness, marketing, finance

Internship Mathematical Optimization focuses on developing and applying algorithms to optimize processes, often in logistics or operations research. Data Analyst Interns analyze and interpret data to support business decisions. While both roles involve data and programming, optimization internships emphasize mathematical modeling, whereas data analysis internships focus on data interpretation and visualization.

What are the most commonly searched types of Mathematical Optimization jobs in New York?

The most popular types of Mathematical Optimization jobs in New York are:

What job categories do people searching Internship Mathematical Optimization jobs in New York look for?

The top searched job categories for Internship Mathematical Optimization jobs in New York are:

What cities in New York are hiring for Internship Mathematical Optimization jobs?

Cities in New York with the most Internship Mathematical Optimization job openings:

Infographic showing various Internship Mathematical Optimization job openings in New York as of August 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Quantitative Researcher - Internship

WallStreetQuants

New York, NY • On-site

Full-time

Re-posted 9 days ago


Job description

About the Internship
A New York based Hedge Fund is seeking an Undergraduate Quantitative Research Intern to join their quantitative research team. This internship is designed for undergraduate students interested in applying mathematics, statistics, programming, and data analysis to financial markets.
You will work alongside experienced researchers and traders to explore market data, test research ideas, and help evaluate systematic trading strategies. This is a hands-on opportunity to gain exposure to quantitative finance in a collaborative and intellectually challenging environment.
Requirements
Responsibilities
  • Analyze financial and market datasets using statistical methods.
  • Assist with research on systematic trading strategies.
  • Clean, organize, and validate large datasets.
  • Build simple models and backtests under researcher supervision.
  • Write Python code for data analysis, visualization, and research workflows.
  • Summarize findings clearly through charts, reports, or presentations.
  • Collaborate with researchers, traders, and engineers on research projects.
  • Learn how quantitative research ideas are developed, tested, and evaluated.
Qualifications
  • Currently pursuing a bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, or a related quantitative field.
  • Expected graduation date of 2028 or 2029.
  • Strong academic performance in quantitative coursework.
  • Programming experience in Python.
  • Familiarity with probability, statistics, linear algebra, or optimization.
  • Interest in financial markets, trading, investing, or data-driven decision-making.
  • Strong problem-solving skills and attention to detail.
  • Ability to communicate technical ideas clearly.
Preferred Qualifications
  • Experience with pandas, NumPy, matplotlib, scikit-learn, or similar tools.
  • Coursework or projects involving data analysis, machine learning, econometrics, or time series.
  • Familiarity with SQL or databases.
  • Participation in math, programming, trading, data science, or research competitions.
  • Prior internship, academic research, or independent project involving quantitative analysis.

Benefits
What You'll Gain
  • Exposure to real-world quantitative research and systematic trading.
  • Mentorship from experienced researchers and traders.
  • Practical experience working with financial data.
  • Opportunity to contribute to meaningful research projects.
  • A deeper understanding of careers in quantitative finance.