We are sharing a specialised remote consulting opportunity for Data Scientists and Quantitative Professionals with expertise in Python, machine learning, statistics, data analysis, and experimentation to contribute their technical knowledge to advanced AI training and evaluation initiatives.
Selected professionals will evaluate AI-generated solutions to statistical, machine learning, and quantitative problems, develop expert-level evaluation tasks, and identify methodological errors in complex analytical reasoning. The work combines practical data science experience with statistical validation, experimental design, and structured technical feedback to improve how advanced AI systems approach quantitative analysis and problem-solving.
Key Responsibilities
Data Science & Quantitative Evaluation
- Evaluate AI-generated solutions to data science, statistical, and quantitative problems.
- Assess the correctness and completeness of analytical methodologies and conclusions.
- Identify flawed assumptions, computational errors, and weaknesses in quantitative reasoning.
- Apply statistical and mathematical principles to evaluate technical problem-solving approaches.
- Provide accurate assessments of AI performance across relevant data science tasks.
Machine Learning & Statistical Analysis
- Review AI-generated machine learning approaches, modelling decisions, and analytical outputs.
- Evaluate the appropriate application of statistical methods and machine learning techniques.
- Identify methodological weaknesses involving model selection, statistical inference, and interpretation.
- Assess whether quantitative conclusions are supported by the underlying calculations and assumptions.
- Apply practical knowledge of machine learning and statistics to improve evaluation quality.
Experimentation & Analytical Reasoning
- Evaluate experimental designs, analytical workflows, and statistical testing approaches.
- Review assumptions, methodologies, and interpretation of experimental results.
- Identify errors in quantitative comparisons, statistical reasoning, and analytical conclusions.
- Assess the logical consistency of AI-generated experimental and modelling recommendations.
- Develop clear explanations of appropriate experimental and analytical methodologies.
Expert-Level Prompt & Dataset Development
- Create technically rigorous prompts covering statistics, machine learning, and quantitative analysis.
- Develop datasets and analytical tasks that challenge AI reasoning and problem-solving capabilities.
- Produce accurate reference solutions with clearly explained methods and calculations.
- Design evaluation scenarios involving realistic data science and computational problems.
- Ensure task specifications and reference answers support consistent technical assessment.
Technical Review, Documentation & AI Quality Assurance
- Document statistical errors, methodological weaknesses, and inaccurate analytical conclusions.
- Provide structured feedback explaining appropriate corrections and alternative approaches.
- Review AI-generated technical explanations for clarity, accuracy, and completeness.
- Communicate complex statistical and machine learning concepts through precise written evaluations.
- Maintain high standards of analytical rigor, consistency, and technical documentation across assigned deliverables.
Ideal Profile
- Professional experience or demonstrated technical expertise in data science, machine learning, quantitative analysis, or a closely related field.
- Strong working knowledge of Python for data analysis and computational problem-solving.
- Experience using pandas or comparable data processing and analytical tools.
- Solid understanding of statistics, probability, and quantitative reasoning.
- Familiarity with machine learning algorithms, modelling techniques, and analytical workflows.
- Experience analysing datasets and interpreting quantitative results.
- Understanding of experimental design, statistical testing, and analytical validation.
- Ability to identify flawed statistical assumptions and methodological inconsistencies.
- Familiarity with data modelling and practical quantitative problem-solving.
- Strong programming skills relevant to implementing and reviewing analytical solutions.
- Ability to explain statistical and machine learning concepts clearly in writing.
- Experience evaluating analytical methodologies and the correctness of quantitative conclusions.
- Strong mathematical reasoning, logical thinking, and attention to detail.
- At least 1 year of professional experience at an established technology, finance, or research company is preferred.
- Recent relevant experience, including work completed within the past 3 years, is particularly valued.
- Experience working with complex analytical problems in professional or research environments.
- Candidates based in an English-speaking country are preferred.
- Excellent written communication skills, particularly when explaining technical and statistical concepts.
- Ability to work independently and provide accurate, structured technical feedback.
- Familiarity with AI model evaluation or technical benchmarking is advantageous.
- Prior experience with AI training projects is not required.
Engagement Details
- Freelance / contract engagement
- Fully remote
- Compensation: $150–$200/hour
- 100 available openings
- Specialised data science consulting role supporting advanced AI training and evaluation.
- Technical Focus: Python, pandas, machine learning, statistics, data analysis, experimentation, and data modelling.
- Evaluation Focus: Statistical correctness, machine learning methodology, quantitative reasoning, and analytical accuracy.
- Preferred Professional Background: At least 1 year of relevant experience at an established technology, finance, or research company.
- Preferred Location: English-speaking countries.
- Responsibilities will include evaluating AI-generated analytical solutions, developing expert-level prompts and datasets, and preparing verified reference answers.
- Assignments will require identifying statistical errors, flawed methodologies, and weaknesses in quantitative reasoning.
- Deliverables may include technical evaluations, structured feedback, analytical tasks, and reference solutions.
- Strong independent problem-solving capabilities and clear technical communication are important for successful project execution.
- Previous experience with AI training projects is not required.
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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