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Department Overview:
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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). |
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Anticipated Start Date:
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Nov 2026 |
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Anticipated End Date (If Applicable):
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May 2027 |
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Remote Work Eligibility Detail:
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All Remote
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Anticipated Hours Per Week:
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Minimum: 10 Maximum: 15 |
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Schedule:
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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. |
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Salary/Wage Range/Lump Sum:
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Minimum: $20.00 |
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Number of Positions:
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3 |
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Qualifications:
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Qualifications & Skills:
1. Currently enrolled student at UW-Madison in Computer Sciences, Data Science, Quantitative Finance, Statistics, Financial Engineering, or a related quantitative field.
2. Strong Python programming skills (PyTorch, Pandas, NumPy, Scikit-learn).
3. Familiarity with financial time-series analysis, econometric models, machine learning or LLM prompt engineering is highly desirable.
4. 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. |
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Knowledge, Skills & Abilities:
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Required Qualifications:
1. Working proficiency in Python, including data manipulation and analysis using pandas and NumPy.
2. A foundational understanding of probability and statistics, including hypothesis testing, confidence intervals, and regression.
3. Familiarity with basic machine learning concepts and evaluation practices, including train/validation/test splits, overfitting, and data leakage.
4. Ability to independently debug code, check results, document procedures, and clearly explain findings.
5. Relevant coursework, research experience, or substantial project experience.
Preferred Qualifications:
Experience in one or more of the following areas is a plus:
1. Time-series analysis and forecasting, including lagged features, rolling-window evaluation, and chronological data splitting.
2. Financial data analysis, quantitative finance, factor research, portfolio modeling, or backtesting.
3. Large language models, including API-based experiments, prompt design, and model evaluation.
4. Statistical methods for comparing models, such as paired comparisons and bootstrap confidence intervals.
5. 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.
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Position Summary/Job Duties:
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Research and Publication Opportunities:
Interns will have opportunities to contribute to experimental design, analysis, and academic writing. Depending on the quality and maturity of the work, 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. Publication, acceptance, and authorship are not guaranteed. 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 1. your research interests and relevant experience; 2. your weekly availability and how long you expect to participate; 3. If available, a link to a GitHub repository, coding project, research report, or paper. Course projects are welcome; 4. whether you have Federal Work-Study eligibility.
Shortlisted applicants may be invited to a brief interview and a small practical task.
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Physical Demands:
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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.
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Institutional Statements:
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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. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals.
The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background-people who as students, faculty, and staff serve Wisconsin and the world.
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:https://employeedisabilities.wisc.edu/disability-accommodation-information-for-applicants/
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