Competitive Data Scientist (Kaggle)

You will create data science and machine learning tasks that require a correct, reproducible solution rather than a plausible answer. Each task should include the data, dependencies, working environment, reference solution, and checks needed to verify completion.

• Build reproducible environments and prepare relevant data and dependencies.
• Implement verified reference solutions for data science and machine learning tasks.
• Write tests and evaluation criteria that separate correct solutions from incomplete or flawed approaches.
• Run coding agents against tasks, investigate failures, and improve tasks based on what you observe.
• Find implementation errors, flawed assumptions, data leakage, and other issues that affect correctness.
• Document task requirements, solution reasoning, and verification steps clearly.

What it pays and takes

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Workload: About 15 hours per week, with flexible scheduling.
• Work setting: Fully remote contractor work, open to candidates in eligible countries across North America, South America, Europe, Africa, Asia, and the Middle East.
• Language: Fluent in English.
• Experience: Listed as entry level, with demonstrated experience in data science, machine learning, quantitative modeling, or research competitions such as Kaggle or DrivenData.
• Skills: Strong problem-solving ability, practical programming skills, and a clear understanding of the methods you use.
• Technical skills: Strong Python skills, including testing, debugging, and working with unfamiliar code.

How it works

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.

The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 10 screening questions.

About AI training work

AI training work is the human side of building artificial intelligence. People prepare data, write and assess code, and review model results so AI systems can produce more reliable answers; OpenTrain helps people find these projects, build a profile, and apply through the platform.