Work directly with AI systems to create high-quality quantitative data and help improve their mathematical and research reasoning. Apply your graduate-level knowledge of probability, statistics, and programming while learning how expert-created data supports AI post-training and evaluation.

What you'll do

Interact with AI models on probability, statistics, quantitative modeling, time-series analysis, and research programming tasks.
Create challenging quantitative problems, reference solutions, and reproducible worked examples.
Check AI-generated mathematics and code, test assumptions, and identify data leakage, overfitting, or flawed backtesting logic.
Compare and annotate model responses, explain errors clearly, and document the reasoning behind a high-quality solution.

What you'll learn

Learn how domain-specific examples and human feedback are used to support AI post-training.
Gain practical experience evaluating AI responses, applying annotation guidelines, and checking dataset quality.
See how factual accuracy, clear reasoning, and consistent feedback help teams assess and improve AI model behavior.
Build experience at the intersection of your academic field and applied AI through project work and feedback.

Work arrangement

Remote internship
Collaborate with the team on scoped AI data and evaluation projects

Project scope, schedule, tools, and expectations will be discussed during the application process. Use only approved materials; do not share confidential employer, client, or university research data.

Requirements

Currently enrolled in a master’s or higher degree program in mathematics, statistics, computer science, quantitative finance, or a related field.
Foundational knowledge of probability, statistics, and linear algebra.
Comfort with Python and data-analysis libraries, or a comparable research programming language.
Ability to explain assumptions, reproduce calculations, and assess limitations honestly.

Alpheva is a new expert network (launched September 2026); payout methods are not published yet, so confirm your first payment before scaling up.

Quant Intern

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