Quant Intern

Alpheva; United States; Remote; USD 28,000 - 41,000; Part time

Job summary

Alpheva is seeking a remote internship inviting a master's or higher student in math, stats, CS, or quantitative fields to work with AI systems on probability, statistics, and data-driven research tasks.

You will evaluate AI outputs, craft reproducible examples, and help improve model reasoning by checking calculations, backtesting logic, and data quality, all while learning how domain expertise guides post-training evaluation.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Probability

Statistics

Linear Algebra

Pandas/NumPy

Research programming

Education

Master's or higher degree

Tools

Python

Jupyter

Job description

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.