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.

• 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