Machine Learning Evaluation Data Analyst

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. It helps people discover projects, build a professional profile, and apply to opportunities in a fast-growing industry where human expertise directly shapes advanced AI systems.

OpenTrain AI is hiring and contracting for this role. Creating an OpenTrain account is free, and your profile can help you showcase relevant experience as you grow your AI training career.

About AI Training and Model Evaluation

AI training is the human side of building artificial intelligence. Contributors prepare, review, and evaluate the data and model behavior that help AI systems become more accurate, reliable, and useful.

In this role, your analysis will support benchmark-driven evaluation of machine learning systems. By examining metrics, distributions, edge cases, and failure modes, you will help teams understand how models behave in real-world scenarios.

The Role

OpenTrain is seeking an ML Evaluation Data Analyst to analyze structured and unstructured data from machine learning training, inference, and evaluation pipelines. You will assess model outputs and performance metrics, investigate benchmark failures, validate data quality, and create rigorous, reproducible analytical work.

This is a remote contractor assignment for candidates located in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, or Mexico. The engagement is planned for three months and may be adjusted based on engagement.

• Employment type: Contractor and part-time
• Time commitment: At least four hours per day and 20 hours per week
• Schedule requirement: Four hours of overlap with PST
• Language: English
• Experience level: Intermediate

What You’ll Do

You will turn complex training, inference, and evaluation data into clear findings that support machine learning research and engineering. Your work will contribute to reliable evaluation workflows and better understanding of model behavior.

• Analyze datasets generated by machine learning training, inference, and evaluation workflows.
• Define, compute, and validate metrics used to assess model performance and behavior.
• Investigate data distributions, edge cases, model outputs, and benchmark failures.
• Use Python and SQL to analyze data, produce reports, and support evaluation workflows.
• Validate data quality, consistency, and correctness across datasets and experiments.
• Create clear analytical artifacts and reproducible analysis workflows.
• Collaborate with machine learning engineers and researchers on challenging evaluation scenarios.

Required Qualifications

This assignment requires at least three years of experience as a data analyst or analytics-focused engineer. You should be comfortable working with large, complex datasets and translating analytical findings into clear written and spoken communication.

• At least three years of experience as a data analyst or analytics-focused engineer.
• Strong Python proficiency for data analysis and reproducible analytical workflows.
• Solid SQL experience with relational datasets.
• Experience analyzing machine learning outputs and evaluation metrics.
• Strong statistical reasoning for investigating distributions, failure modes, and edge cases.
• Ability to validate complex datasets and assess data consistency and correctness.
• Ability to write clean, readable, well-documented analytical code.
• Clear spoken and written English communication.

Who Should Apply

This opportunity is suited to experienced data analysts and analytics-focused engineers who enjoy investigating why machine learning systems succeed or fail. It is especially relevant if you combine strong Python and SQL skills with statistical judgment and an interest in rigorous model evaluation.

• Data analysts with experience working on machine learning evaluation.
• Analytics-focused engineers who build reproducible workflows.
• Professionals comfortable investigating model behavior and benchmark results.
• Candidates who can communicate complex findings clearly to technical collaborators.

Remote Contract Details

The assignment is remote and available only in the listed countries. You must be able to contribute at least 20 hours each week, work at least four hours per day, and provide four hours of overlap with PST during the engagement.

• India
• Pakistan
• Nigeria
• Kenya
• Egypt
• Ghana
• Bangladesh
• Turkey
• Brazil
• Mexico

Build Your AI Training Career

AI evaluation and data analysis are part of a rapidly growing field built around improving how artificial intelligence works. OpenTrain gives you a place to build a credible profile, discover relevant projects, and develop a portfolio of work that supports longer-term growth in AI training and data labeling.

• Work remotely with a flexible part-time structure.
• Apply analytical and statistical skills to cutting-edge AI systems.
• Build experience evaluating real-world machine learning behavior.
• Create an OpenTrain profile to support future opportunities.