Competitive Data Scientist

You will create and validate challenging data science tasks used to assess coding agents and data science skills. The work turns competition-grade reasoning into reproducible environments, reference solutions, reliable tests, and clear verification rules.

• Build reproducible environments with the required data, dependencies, and execution steps.
• Implement verified reference solutions showing how each task should be completed.
• Create tests and evaluation criteria that separate correct solutions from incomplete or flawed approaches.
• Run coding agents against tasks, investigate failures, and improve task designs based on their behavior.
• Find implementation errors, flawed assumptions, data leakage, and other issues that affect correctness.
• Document task requirements, solution reasoning, and verification steps clearly.

This is a remote contractor role with a flexible schedule. The structured experience level is entry level, while the work requires practical data science, programming, testing, debugging, and solution-verification skills.

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Time: Less than 20 hours per week, with an expected commitment of about 15 hours per week.
• Schedule: Choose the hours and days you work.
• Location: Open to candidates in Algeria, Argentina, Austria, Bahrain, Bangladesh, Belgium, Brazil, Canada, Chile, Colombia, Denmark, Egypt, France, Germany, Ghana, Greece, India, Indonesia, Italy, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Lebanon, Malaysia, Mexico, Morocco, the Netherlands, Nigeria, Oman, Pakistan, Palestinian Territories, Peru, the Philippines, Portugal, Qatar, Saudi Arabia, Singapore, South Africa, Spain, Sri Lanka, Switzerland, Taiwan, Thailand, Tunisia, the United Arab Emirates, the United Kingdom, the United States, Uzbekistan, and Vietnam.
• Language: Professional fluency in English.
• Required background: Experience in data science, machine learning, quantitative modeling, or research competitions.
• Competition experience with platforms such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench.
• Strong problem-solving skills and a clear understanding of the methods used in your solutions.
• Programming ability to implement, test, and verify solutions independently.
• Strong Python skills, including testing, debugging, and working with unfamiliar code.
• Helpful experience includes published competition solutions, a strong competitive data science profile, notable rankings, applied mathematics, machine learning engineering, or quantitative research paired with hands-on implementation and verification skills.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

OpenTrain is a platform where people find AI-training and data-labeling projects, build a profile, and apply. AI training work uses human-created examples, reviews, and evaluations to help artificial intelligence systems produce more useful and reliable results.