Undergraduate Intern Quantitative Data & Finance (Cross-Disciplinary

Position Overview We are seeking an undergraduate student to support our Finance and IT teams with a focus on data analysis and quantitative problem-solving . This internship provides hands-on experience working with financial datasets, basic modeling, and tools used in data-driven decision-making. We welcome candidates from analytical and cross-disciplinary backgrounds —including mathematics, applied mathematics, statistics, economics, engineering, computer science, physics, astrophysics, quantum computing, biotech and other data-driven fields—who are interested in applying quantitative thinking to real-world business and financial problems. Key Responsibilities Work with structured datasets to support basic financial and operational analysis Assist in organizing, cleaning, and validating data for reporting and modeling Build and maintain spreadsheets and simple analytical models in Excel Support development of reports, dashboards, and visualizations Identify patterns, inconsistencies, or trends in data Assist with automation or efficiency improvements using tools like Excel, SQL, or Python (where applicable) Collaborate with team members on data, finance, and technology-related tasks Apply quantitative or analytical approaches from coursework to practical business problems Required Qualifications Currently pursuing a Bachelor's degree in a quantitative or analytical field (e.g., Mathematics, Applied Mathematics, Physics, Astrophysics, Statistics, Economics, Computer Science, Quantum Computing, Engineering, Finance, Biotech, or other data-driven discipline) Strong problem-solving and analytical thinking skills Familiarity with: Microsoft Excel (formulas, basic functions) Microsoft Office (Word, PowerPoint) Comfort working with numbers and structured data Strong attention to detail and willingness to learn Preferred Qualifications Exposure to programming or data tools (Python, SQL, R, or similar) through coursework or projects Experience with Excel functions (e.g., VLOOKUP, pivot tables) Introductory knowledge of statistics, probability, or data analysis Interest in financial markets, data analytics, or fintech Coursework or projects involving: Data analysis or visualization Mathematical modeling Machine learning (introductory) Computational or applied problem-solving What You'll Gain Hands-on experience applying quantitative skills in a real-world business environment Exposure to financial data, analytics workflows, and decision-making processes Opportunity to build foundational data and modeling skills Mentorship and professional development Insight into career paths in quantitative finance, data science, and analytics Internship Details Summer 2026, with possible extension