Data Science, Quantitative AI Evaluation Specialist

Gramian Consulting

. Evaluate AI-generated outputs across data science, statistics, machine learning, experimentation, and quantitative problem-solving .

Posted 10/14/2026contractRemote • United States, Canada, United Kingdom, Australia, New ZealandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in evaluating AI-generated outputs through data science, statistics, and machine learning, while providing structured feedback to enhance AI model capabilities. Strong analytical skills are essential for identifying errors and communicating technical findings effectively.

Highest-signal resume keywords

Data ScienceMachine LearningStatistical AnalysisAnalytical Problem-SolvingTechnical Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningStatisticsQuantitative AnalysisAnalytical EvaluationPrompt EngineeringDataset CreationStatistical MethodologiesQuantitative ReasoningEvidence-Based Feedback

Soft Skills

Analytical ThinkingCritical ThinkingClear CommunicationAttention to DetailSystematic Evaluation

Industry Keywords

AI EvaluationData-Driven ReasoningTechnical FindingsTop Company ExperienceEnglish Proficiency

About the role

Key responsibilities & impact

Evaluate AI-generated outputs across data science, statistics, machine learning, experimentation, and quantitative problem-solving
Create expert-level prompts, datasets, and reference solutions for AI training and evaluation
Identify flawed methodologies, statistical inaccuracies, unsupported assumptions, and weaknesses in quantitative reasoning
Assess the correctness, reliability, and clarity of analytical approaches and conclusions
Provide structured, evidence-based feedback to help improve AI model capabilities
Apply consistent evaluation criteria and communicate technical findings clearly

Requirements

What you’ll need

At least one year of experience working at a top company (tech, finance, or research), and 3 years of experience (overall) working in DS/SWE
Bachelor’s degree in Data Science, Software Engineering, or a related field from a university in the United States, Canada, Australia, New Zealand, or the United Kingdom
Foundational knowledge of data science, statistics, machine learning, or quantitative analysis
Strong analytical and critical-thinking skills, with the ability to identify errors in data-driven reasoning
Excellent written English and the ability to explain technical and statistical concepts clearly
Ability to evaluate complex problems systematically and provide accurate, well-supported feedback
Current residence in an English-speaking country