Junior Data Scientist

$150–200/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Worldwide
Field: STEM and Coding

Evaluate AI outputs across data science, statistics, machine learning, experimentation, and quantitative reasoning. The contract also involves creating prompts, datasets, reference solutions, and structured technical feedback.

The work

This remote contractor role focuses on assessing whether AI-generated answers use sound statistical methods, machine learning concepts, experimental designs, and quantitative reasoning. Day to day, you may review model outputs, locate methodological or statistical errors, create expert-level prompts and datasets, write reference solutions, and document how an answer should improve.

What the screening emphasizes

Expect verification of your professional background and detailed follow-up on technical examples. The platform is likely to test whether you can distinguish a merely plausible answer from a defensible one, identify issues such as leakage or invalid inference, and explain corrections clearly enough to support model evaluation.

Preferred background

The listing prefers at least one year of experience at a top company in technology, finance, or research, with some of that experience occurring within the past three years. It also prefers candidates based in an English-speaking country and asks for clear written communication of technical and statistical concepts.

Logistics

The engagement is remote and structured as contractor work. The listing does not specify whether tasks are fully asynchronous, how many hours are typically available, or whether there are fixed working windows, so candidates should be ready to state their availability and confirm scheduling expectations during screening.

Pay band: $150–200/hr

What they look for

Python
Machine Learning
Statistics
Data Analysis
Experimentation
Pandas
Data Modeling

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This checks whether the claimed company experience, recency, and quantitative responsibilities are concrete enough to verify under follow-up.
A strong answer: Give a concise timeline with employer type, dates, role scope, and one or two representative projects. Separate your own decisions and outputs from the work of the wider team.
Where people lose it: Candidates lose credibility by naming prestigious organizations without dates, project specifics, or a clear account of their individual contribution.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

STEM AND CODING on Sidequest

What stem and coding AI work pays

Rates by specialty, the platforms hiring, and every open role in this field.