DRW - Quantitative Research Intern
Requirements
• Are pursuing a Bachelor’s, Master’s or PhD in a technical discipline with a focus on Statistics, Optimisation, Machine Learning, Artificial Intelligence, Quantitative Finance or related fields graduating between December 2027 and October 2028 • December 2027 • October 2028 • Proficiency in Python programming experience using the Python machine learning stack: numpy, pandas, scikit-learn, etc. • Proficient programming skills with experience exploring large datasets • Strong analytical and problem-solving skills including a solid foundation of statistics knowledge • Working knowledge of probability theory, stochastic calculus and numerical algorithms such as finite differences, Monte Carlo simulation, etc. • Some exposure to Natural Language Processing and/or High-Performance Computing is a plus • Excellent written and verbal communication skills to report research results as well as methodologies • Added bonus if you have been published in a top tier journal focusing on Natural Language Processing or High-Performance Computing • What to expect during the internship • Meaningful projects: Each project, advised by a trader, promotes a comprehensive learning experience and provides you with real-world work experience. • Meaningful projects: • Housing: DRW provides fully furnished apartments located close to the office – making your morning commute as easy as possible. • Housing: • Mentorship: You’ll build a professional relationship with an experienced mentor in your field. Mentors and mentees meet to discuss goals, challenges and professional development and explore the city together at our mentor outings. • Mentorship: • Education: As the trading industry continually evolves, both in terms of new products and transaction methods, the future will present us with unique opportunities and challenges. You’ll complete an options course taught by an experienced trader and participate in a technology immersion course to better understand how technology and trading intersect. • Education: • DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. • Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. • We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. • For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice. • For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice • California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice. • California residents, please review the California Privacy Notice for information about certain legal rights at • https://drw.com/california-privacy-notice.
Responsibilities
• Create practical solutions to problems presented in the trading environment on either a systematic equity trading desk or a fixed income options desk • Conduct statistical analysis of market data, historical trends, and relationships across multiple asset classes • Formulate and apply mathematical modeling, quantitative methods and machine learning techniques to identify and capture trading opportunities • Work closely with traders and researchers to build and refine research infrastructure and tools
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