Data Scientist Mathematical Statistics Python

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. OpenTrain helps people start and grow careers teaching AI through flexible, remote projects across the industry.

• Apply through OpenTrain and create an account for free.
• Work remotely from anywhere worldwide.
• Build experience in a fast-growing field supporting the development of modern AI systems.

About AI Training and Data Work

AI training is the human side of building artificial intelligence. Contributors analyze examples, evaluate model outputs, review code, and provide structured feedback so AI systems can become more accurate and useful.

In this role, your statistical analysis and clear explanation of evidence can support the evaluation of AI-related data and systems. The work is flexible and remote, making it suitable for people building experience in data science alongside other commitments.

• Contribute to cutting-edge AI development through analytical and evaluation work.
• Use human judgment to assess data, methods, results, assumptions, and limitations.
• Choose a part-time workload of fewer than 20 hours per week.

The Role

OpenTrain AI is seeking an entry-level Data Scientist with a strong foundation in mathematical statistics and strong Python skills. You will clean and wrangle datasets, choose appropriate statistical tests, run analyses with scipy and statsmodels, and extract actionable insights.

The role requires you to interpret results carefully and communicate assumptions and limitations clearly. You will also maintain reproducible notebooks, document methods, and summarize findings for stakeholders through clear narratives and visual summaries.

• Contractor and part-time position
• Pay: $25 USD per hour
• Time requirement: fewer than 20 hours per week
• Worldwide opportunity
• Primary language: English

What You'll Do

You will apply statistical inference and data science techniques to practical analysis tasks. Work may include assessing experiments, modeling relationships, checking assumptions, and turning complex results into understandable conclusions.

• Clean, wrangle, and explore messy datasets.
• Select and run appropriate statistical tests in scipy and statsmodels.
• Design or assess experiments, including A/B tests.
• Compute and interpret p-values, confidence intervals, effect sizes, and statistical power.
• Fit and evaluate linear and logistic regression models.
• Analyze correlations using Pearson and Spearman methods.
• Work with probability distributions, normality checks, and non-parametric methods.
• Check model assumptions and diagnostics.
• Create visual summaries and clear stakeholder-facing narratives.
• Maintain reproducible notebooks and document analytical methods.

Requirements

You should have strong Python skills for analysis and a solid foundation in mathematical statistics. You must be comfortable interpreting statistical results, explaining assumptions and limitations, and communicating analytical findings clearly.

• Strong Python skills with numpy, scipy, statsmodels, and pandas
• Mastery of hypothesis testing, including t-tests, chi-square tests, ANOVA, and appropriate post-hoc methods
• Ability to calculate and interpret p-values, confidence intervals, and effect sizes
• Proficiency with Pearson and Spearman correlation and linear and logistic regression
• Understanding of probability distributions, normality checks, and non-parametric methods
• Experience with exploratory data analysis and cleaning messy data
• Knowledge of experimental design, A/B testing, and power analysis
• Reproducible workflows using notebooks, version control, and clear documentation
• Strong analytical writing and ability to explain assumptions and limitations
• SQL for data extraction and joins is a plus

Who Should Apply

This opportunity is designed for entry-level candidates who can combine practical Python analysis with sound statistical reasoning. It may suit data scientists, statisticians, analysts, or technically minded contributors who enjoy evaluating evidence and explaining results.

• Candidates with strong mathematical statistics knowledge
• Python practitioners who use data analysis libraries confidently
• Analysts who can communicate technical findings to stakeholders
• People seeking flexible, remote, part-time work in AI training and evaluation

How to Get Started

Create a free OpenTrain account to apply. If selected, you will work as a contractor on a flexible, part-time project supporting AI training through statistical analysis, evaluation, and reproducible documentation.

• Apply through OpenTrain.
• Review the role requirements and demonstrate your Python and statistics capabilities.
• Complete qualifying steps as requested for the project.
• Work remotely for fewer than 20 hours per week at $25 USD per hour.