Remote | Data Scientist — $245–$280/hour

24-Mag • New York, NY

6h • Remote

About The Position

This remote independent-contractor consulting engagement supports an advanced AI training and quantitative reasoning project. The Data Scientist will evaluate how AI systems approach statistical, machine-learning, and quantitative problems; develop rigorous prompts, datasets, and reference solutions; and identify methodological or analytical weaknesses in model outputs. The work calls for strong quantitative judgment, careful statistical reasoning, and clear written communication.

Assignments may cover data-science evaluation, statistical reasoning, machine learning, experimentation, prompt development, dataset creation, and reference-solution development. Project scope, workload, analytical focus, and evaluation standards may change with project requirements. Work must not use confidential or proprietary information belonging to an employer, client, company, research organization, institution, or other third party.

Requirements

• At least 1 year of professional experience in data science, quantitative analysis, machine learning, or a closely related role at a top-tier or highly regarded organization.
• At least part of the relevant professional experience should have been gained within approximately the past 7 years.
• Strong proficiency in Python.
• Strong knowledge of statistics, experimentation, and quantitative analysis.
• Practical experience with machine learning and data modelling.
• Familiarity with pandas and modern data-analysis workflows.
• Strong ability to identify methodological errors and weak statistical reasoning.
• Excellent written communication and ability to explain technical concepts clearly.

Nice To Haves

• An undergraduate degree from a highly ranked university is preferred.
• Experience gained in technology, finance, research, or a comparable quantitative environment may be relevant.
• Candidates based in English-speaking countries are preferred.

Responsibilities

• Evaluate AI-generated responses to data-science, statistics, machine-learning, and quantitative problems for technical soundness, numerical accuracy, logical consistency, and appropriate use of evidence.
• Identify flawed methodology, incorrect statistical reasoning, unsupported interpretations, and weaknesses in assumptions or conclusions.
• Assess machine-learning reasoning and predictive analyses, including model choices, overfitting, data leakage, bias, validation, and metric selection; explain relevant trade-offs between analytical approaches.
• Create expert-level prompts and datasets or scenarios that rigorously evaluate quantitative and analytical capabilities.
• Develop high-quality, reproducible, technically defensible reference solutions, clearly documenting assumptions, calculations, and methodology.
• Evaluate experiment design, hypothesis testing, results interpretation, analytical workflows, data preprocessing, feature construction, and data-modelling approaches.
• Identify weaknesses in experimental setup, measurement, or causal interpretation, including in ambiguous or incomplete data scenarios.
• Provide structured written feedback on errors, weaknesses, and improvement opportunities; identify recurring patterns of flawed reasoning and contribute evaluation material to improve model capability.
• Maintain consistent evaluation standards across diverse data-science and quantitative tasks.

What This Job Offers

• Career Level: Mid Level
• Education Level: No Education Listed