Senior Data Scientist and Data Engineering Experts

$120–180/hr

rate as listed

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

Design realistic data science and data engineering tasks, then create precise criteria for evaluating AI-generated work. The project covers analysis, modeling, experimentation, ETL, pipelines, and Python and SQL workflows.

What the work involves

You will create challenging, realistic assignments based on real-world data science and data engineering practice. Subjects may include exploratory analysis, statistical modeling, machine learning pipelines, ETL, data pipeline design, experimentation or A/B test write-ups, and Python and SQL workflows.

You will also define task-specific evaluation criteria that show what a strong deliverable should contain. Day-to-day review work requires applying those criteria consistently, documenting evidence for judgments, and revising submissions in response to feedback from senior reviewers.

What Mercor screens for

The screen is likely to emphasize verifiable experience at a qualifying technology, quantitative, financial, consulting, or Fortune 100 employer, followed by detailed discussion of projects and technical decisions. The ideal profile calls for strong command of Python and SQL, depth in statistical modeling, machine learning, experimentation and causal inference, and excellent written English.

Logistics

Pay band: $120–180/hr

This reflects the listed band and does not guarantee work volume or compensation. Candidates must be based in the United States, United Kingdom, Canada, Australia or New Zealand. The listing does not state whether the engagement is remote, whether collaboration is asynchronous, or the typical weekly hours.

What they look for

4+ years of professional data science, data engineering or machine learning experience in a qualifying firm and role
Python and SQL
Statistical modeling, machine learning, experimentation and causal inference
ETL and reliable data pipeline design
Rigorous analysis of messy real-world data
Clear technical writing in English

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 tests whether the claimed 4+ years and qualifying employer or seniority path can be verified without relying on broad team-level accomplishments.
A strong answer: Give a chronological account with employer type, exact title, dates and two or three responsibilities you personally owned. Distinguish your work from the wider team's output and identify whether each role centered on data science, engineering or machine learning.
Where people lose it: Candidates lose points by naming prestigious employers but leaving dates, title level or personal ownership unclear.

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.