Data Science & Analysis - AI Training - Sheffield, UK

prolificacademicltd; United States; Remote; USD 55,000 - 110,000; Full time

Benefits offered by this job

Remote work

Job summary

prolificacademicltd seeks practitioners to review AI-generated data insights and statistical analyses, ensuring accuracy, clarity, and completeness. You will run Python or R scripts to verify results and test edge cases, and assess how models reason through data problems, documenting strengths and weaknesses.

The role requires a strong background in data science, statistics, or related fields, with experience using large language models in data workflows and a focus on precise mathematical

Qualifications

• Bachelor-level or higher in a quantitative field is required.
• Experience with data analysis, predictive modelling or ML engineering is expected.
• Ability to interpret advanced data visualisations and solve complex stats problems.
• Experience using large language models in data workflows and understanding failure modes.
• Strong communication of mathematical concepts and findings; PayPal for payments is required.

Responsibilities

• Evaluate AI-generated data insights and statistical analyses for accuracy and clarity.
• Check mathematical and statistical claims against references.
• Run Python or R scripts to verify results and test edge cases.
• Assess how models reason through data problems and document strengths/weaknesses.
• Review responses for compliance with guidelines and professional standards.

Skills

Data analysis

Predictive modelling

Machine learning engineering

Statistical reasoning

Data visualisation interpretation

Language models in data workflows

Communication of math concepts

Attention to detail

Education

Bachelor's degree in data science, statistics, mathematics or related field

Master's degree in data science, statistics, mathematics or related field

Doctoral degree in data science, statistics, mathematics or related field

Tools

Python

R

SQL

Tableau

Power BI

Matplotlib

Seaborn

PyTorch

TensorFlow

Job description

Role overview

Apply data science or analysis expertise to review and improve AI-generated technical work. Assignments include assessing statistical reasoning, data insights, code, and predictive modelling, with attention to correctness, clarity, and adherence to task guidelines. Candidates complete a short skills assessment before being invited to participate in paid tasks.

Responsibilities

• Evaluate AI-generated data insights and statistical analyses for accuracy, clarity, and completeness.
• Check mathematical and statistical claims against authoritative references.
• Run data-related Python or R scripts to verify results and test edge cases.
• Assess how models reason through data problems and build predictive models, documenting strengths and weaknesses.
• Review responses for compliance with specified guidelines and professional standards.

Requirements

• A bachelor’s, master’s, or doctoral degree in data science, statistics, mathematics, or a related quantitative field.
• Practical experience in data analysis, predictive modelling, or machine-learning engineering.
• Ability to solve complex statistical problems and independently interpret advanced data visualisations.
• Strong attention to detail, including the ability to spot flawed reasoning in statistical arguments and data interpretations.
• Substantial experience using large language models in data workflows, with an understanding of their common failure modes.
• Clear communication of mathematical concepts and analytical findings; a PayPal account is needed to receive task payments.

Nice to have

• Proficiency in Python, including common data and machine-learning libraries, or R; advanced SQL; and data visualisation tools such as Tableau, Power BI, Matplotlib, or Seaborn.
• Knowledge of machine-learning frameworks such as PyTorch or TensorFlow and statistical modelling methods.

Benefits and work setup

Tasks are paid, with advertised rates of up to $80 per hour; rates may vary by assignment. Some work requires one uninterrupted hour, though many tasks are shorter. The arrangement is described as flexible and remote, subject to available assignments.