[Hiring] AI & Quantitative Finance Research Intern @Part-Time, Remote at UW–Madison

Role Description

Ivy Online Inc. is an ed-tech and applied AI research enterprise expanding its focus into FinTech, LLM Evaluation, and Quantitative Financial Modeling. We lead agile, publication-oriented research projects examining counterfactual LLM reliability, econometric time-series models, and market analytics. Our research initiatives aim to submit high-impact findings to top-tier AI and financial technology venues (such as AAAI, NeurIPS, and FinTech conferences).

• Anticipated Start Date: Nov 2026
• Anticipated End Date: May 2027
• Remote Work Eligibility: All Remote
• Anticipated Hours Per Week: Minimum: 10, Maximum: 15
• Schedule: Weekly Total: 10 – 15 hours / week
• Schedule Pattern: Flexible / Self-paced
• Meeting Availability: Mon–Fri, flexible evening or weekend check-ins available.
• Exam Policy: Reduced hours or temporary pause allowed during midterms and finals.
• Salary/Wage Range: Minimum: $20.00
• Number of Positions: 3

Qualifications

• Currently enrolled student at UW-Madison in Computer Sciences, Data Science, Quantitative Finance, Statistics, Financial Engineering, or a related quantitative field.
• Strong Python programming skills (PyTorch, Pandas, NumPy, Scikit-learn).
• Familiarity with financial time-series analysis, econometric models, machine learning or LLM prompt engineering is highly desirable.
• Self-motivated, resourceful in troubleshooting code, and disciplined with modular Git-based workflows.
• Federal Work-Study: We are a UW–Madison Federal Work-Study partner. Students with work-study eligibility are encouraged to apply. Applicants without work-study funding will also be considered, including master’s and PhD students.

Requirements

• Working proficiency in Python, including data manipulation and analysis using pandas and NumPy.
• A foundational understanding of probability and statistics, including hypothesis testing, confidence intervals, and regression.
• Familiarity with basic machine learning concepts and evaluation practices, including train/validation/test splits, overfitting, and data leakage.
• Ability to independently debug code, check results, document procedures, and clearly explain findings.
• Relevant coursework, research experience, or substantial project experience.
• Preferred Qualifications: Experience in one or more of the following areas is a plus:
• Time-series analysis and forecasting, including lagged features, rolling-window evaluation, and chronological data splitting.
• Financial data analysis, quantitative finance, factor research, portfolio modeling, or backtesting.
• Large language models, including API-based experiments, prompt design, and model evaluation.
• Statistical methods for comparing models, such as paired comparisons and bootstrap confidence intervals.
• Research reproducibility tools and practices, including Git, experiment tracking, and clear technical documentation.
• Applicants are not expected to have experience in all of these areas. Strong coursework or independent projects demonstrating relevant skills are welcome. Prior research experience is a plus; publications are not required.

Benefits

• Interns will have opportunities to contribute to experimental design, analysis, and academic writing.
• Projects may lead to submissions to AI and related research conferences or workshops.
• Coauthorship will be based on substantive contributions and the target venue’s authorship requirements.
• Competitive compensation at $20.00 / hour.
• This position offers an opportunity to contribute to ongoing research projects, take responsibility for specific research tasks, and gain hands-on experience in conducting experiments, analyzing data, and preparing academic manuscripts.

How to Apply

• Please submit your résumé or CV and a personal statement.
• In the personal statement, please describe:
• Your research interests and relevant experience.
• Your weekly availability and how long you expect to participate.
• If available, a link to a GitHub repository, coding project, research report, or paper. Course projects are welcome.
• Whether you have Federal Work-Study eligibility.
• Shortlisted applicants may be invited to a brief interview and a small practical task.

Physical Demands

• Prolonged periods of sitting at a desk and working on a computer.
• Frequent use of computer peripherals (keyboard, mouse, monitor) for programming and research analysis.
• Must be able to participate in virtual team meetings via video conferencing.

Institutional Statements

• Equal Employment Opportunity Statement: UW-Madison is an Equal Employment, Equal Access Employer committed to increasing the diversity of our workforce.
• Institutional Statement on Diversity: Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community.
• The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background.
• For more information on diversity and inclusion on campus, please visit: diversity.wisc.edu
• Accommodation Statement: If you need to request an accommodation because of a disability, you can find information about how to make a request at the following website: Disability Accommodation Information for Applicants .