Undergraduate Intern - Quantitative Data & Finance (Cross-Disciplinary

Job Description

Job Description

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.

• 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 

• 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 

• 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 

• 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 

• Summer 2026, with possible extension