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Quantitative Research Summer Internship 2026

Job Location

Vilnius, Lithuania

Employment Type

Internship

Work Setup

Office

Start Date

Summer 2026

​About Us

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VNTrading is a quantitative trading firm that leverages algorithms and low-latency technologies to provide liquidity in financial markets. We trade proprietary capital and rely entirely on our engineering and research to generate consistent returns.

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If you're excited about uncovering patterns in data, building models that respond to real market dynamics, and seeing your research translate into trading strategies, you’ll love it here.

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Internship Overview

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As a Quantitative Research Summer Intern at VNTrading, you will gain hands-on experience in statistical modeling, data analysis, and financial market research. Working closely with experienced researchers and traders, you will help develop, test, and refine systematic trading strategies.

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Throughout our intensive 6-week program, you will work on meaningful, high-impact projects that contribute directly to the firm’s performance.

This is an opportunity to experience how a professional quantitative trading desk operates - fast-paced, rigorous, and deeply analytical - while building the foundation for a career in quantitative finance.

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How You Will Make an Impact

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  • Research and analyze large, high-frequency and historical datasets to uncover patterns and inefficiencies in financial markets

  • Apply statistical modeling, mathematical techniques, and machine learning methods to real trading problems

  • Contribute to the enhancement of research infrastructure, tools, and workflows used by the trading team

  • Lead a dedicated project, allowing you to contribute directly to the firm's growth while demonstrating your technical and creative abilities

  • Collaborate directly with traders and quantitative researchers on the development and improvement of systematic trading strategies

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What You Bring to the Team

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  • Currently studying Mathematics, Statistics, Computer Science, Physics, Engineering, or another quantitative discipline

  • Proficiency in Python, R, MATLAB, or another language for data analysis

  • Good understanding of probability and statistics concepts

  • Passion for solving complex problems using data-driven approaches

  • Genuine interest in financial markets and algorithmic trading

  • Self-motivated, responsible, and comfortable working in a fast-paced, results-oriented environment

  • Eagerness to take responsibility and deliver high-quality work

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What to Expect During the Internship

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Meaningful Projects

Each intern leads a high-impact research project designed to provide hands-on experience with real trading challenges and measurable outcomes.

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Mentorship & Collaboration

You’ll receive close guidance from experienced researchers and traders who are invested in your development and success.

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Learning & Exposure

Gain practical insight into market microstructure, systematic trading, and the research-to-production pipeline in a professional quant firm.

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Ownership & Impact

Your work goes beyond experimentation- strong ideas can move directly into live trading and have a real impact.

 

What We Offer

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  • Salary: €4,000 gross per month

  • Structured and fast-paced 6-week program

  • Hands-on training in markets and trading

  • Support from mentors who want to see you succeed

  • Real ownership and real impact from day one

  • A friendly, collaborative culture where good ideas can come from anyone

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Get in Touch.

Please note that VNTrading is a proprietary trading firm and is not soliciting customers or customer relationships by means of this website or otherwise. Furthermore, VNTrading is not offering any securities or other financial products for sale nor is it soliciting any transactions or investment through this website. The information on this website is not intended to constitute investment advice. VNTrading maintains this website for informational purposes only and undertakes no obligation regarding the information contained herein

© 2025 VNTrading. All Rights Reserved. 

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