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Intern Quantitative Modeling Jobs in Washington, DC

WSP

Transportation Planning Intern - Fall 2026

Washington, DC · On-site

$17.50 - $22.75/hr

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Responsibilities may include collecting and analyzing quantitative and qualitative data, developing ... as tables, charts, accurate reports, models, infographics, and 3D illustrations for the ...

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Intern Quantitative Modeling information

What is an intern quantitative modeling?

Intern Quantitative Modeling positions are internship roles where students or recent graduates work with experienced quantitative analysts to develop and implement mathematical models that assist in financial decision-making, risk management, or trading strategies. Interns typically use statistical, programming, and analytical skills to analyze large data sets and help solve real-world financial problems. These internships offer hands-on experience with quantitative tools, exposure to industry practices, and opportunities to learn from professionals in fields such as finance, insurance, or technology.

What does an intern quantitative modeling do?

As an Intern in Quantitative Modeling, you can expect to assist with developing, testing, and validating mathematical models used for financial analysis, risk assessment, or trading strategies. Typical tasks include working with large datasets, coding in programming languages such as Python or R, and collaborating with senior analysts or data scientists to solve real-world business problems. You'll often participate in team meetings, present your findings, and receive feedback to refine your models. This hands-on experience will help you build strong technical and analytical skills, while giving you exposure to the collaborative nature of quantitative teams in finance or technology firms.

What are the key skills and qualifications needed to thrive as an intern quantitative modeling?

To thrive as an Intern in Quantitative Modeling, you need a solid foundation in mathematics, statistics, and programming, often supported by coursework in quantitative fields like finance, engineering, or computer science. Familiarity with tools such as Python, R, MATLAB, and experience with statistical modeling libraries or financial data systems is highly valuable. Strong analytical thinking, attention to detail, and effective communication skills distinguish top candidates in this role. These skills and qualities are crucial for accurately analyzing complex data, building reliable models, and clearly presenting findings to support business or research decisions.

What is the difference between Intern Quantitative Modeling vs Intern Data Analysis?

AspectIntern Quantitative ModelingIntern Data Analysis
Required SkillsMathematics, programming, financial modelingData manipulation, statistical analysis, visualization
Work EnvironmentFinance, investment banks, hedge fundsTech companies, consulting firms, research institutions
Typical TasksBuilding models, forecasting, risk assessmentData cleaning, reporting, trend analysis

Intern Quantitative Modeling and Intern Data Analysis roles often overlap in skills like programming and data handling. However, quantitative modeling focuses more on creating financial or mathematical models used for decision-making, while data analysis emphasizes interpreting data to uncover insights. Both roles are common in finance and tech industries, but they serve different strategic purposes.

What are the most commonly searched types of Quantitative Modeling jobs in Washington, DC?

The most popular types of Quantitative Modeling jobs in Washington, DC are:

Intern Quantitative Modeling jobs near you

WBG Pioneer - Geospatial Data Analysis Intern

The World Bank Group

Washington, DC • On-site

Internship

Re-posted 3 days ago

Job description

The Trade Policy and Facilitation Unit is developing a quantitative spatial model to assess the spatial economic impacts of logistics infrastructure, logistics and trade facilitation policies, and trade policies at the national and regional levels. Building on a cities spatial model developed jointly by the International Growth Centre (IGC) and the World Bank, the unit intends to extend this framework beyond the city level and to develop it in partnership with the Development Economics (DEC) group, the Transport global practice, and external partners. The model is intended to complement the unit's existing computable general equilibrium (CGE) analysis. 

This work also builds on a long tradition of World Bank analysis of the sub-national geography of trade, including work on lagging regions and their connection to global markets, and seeks to capture the substantial methodological and data advances that have emerged since. Robust spatial analysis of this kind depends critically on the assembly, cleaning, and structuring of high-quality geospatial data used to parameterize and run the model. 

The intern will support this effort within the Trade Policy and Facilitation Unit, contributing to the compilation and preparation of geospatial datasets and to the operation of the quantitative spatial model, under the supervision of the project team. 

Duties and Responsibilities 

Under the guidance of the project lead, the intern will: 

Compile, clean, and structure the geospatial data required to parameterize and run the quantitative spatial ("cities") model, extending it from the city level to the national and regional levels. 

Assemble and process key spatial inputs - including road and transport networks, population grids, terrain data, port and trade-node locations (e.g., PortWatch), and travel-time layers - into model-ready formats. 

Run the spatial model with the prepared data to assess the spatial economic impacts of logistics infrastructure, trade facilitation measures, and trade policies, in coordination with DEC, Transport, and external partners. 

Construct population-weighted accessibility and remoteness indicators to key trade nodes and correlate them with granular socio-economic data. 

Produce maps, interactive dashboards, and other visual outputs to support diagnostics, model validation, and dissemination. 

Contribute to note writing, presentations, and other analytical and dissemination products, and document data sources, methods, and code for reproducibility. 

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