Data Scientist Talent Network
Mercor is building a network of experienced data scientists for potential future projects with leading AI research organizations. These projects may focus on evaluating how effectively AI systems perform real-world data science work.
There is no immediate project opening, but qualified applicants may be contacted as relevant opportunities become available.
2. Potential Responsibilities
Future projects may involve
- Designing precise, task-specific grading criteria for data science deliverables, including exploratory data analyses, statistical modeling work, machine learning pipelines, experimentation and A/B test write-ups, feature engineering, and technical reports or notebooks
- Evaluating AI-generated or human-created work against established criteria
- Providing detailed written justifications for evaluations and scores
- Applying consistent, evidence-based judgment so that assessments are reproducible and defensible
- Incorporating structured feedback from senior reviewers and iterating on submitted work
Specific responsibilities will vary depending on the project.
3. Ideal Qualifications
- 1+ years of professional data science experience
- Experience at a leading technology, research, or quantitative firm (such as top FAANG, AI labs, top-tier quant funds, or equivalent)
- Strong command of Python, SQL, statistical modeling, machine learning, experimentation and causal inference, and translating messy real-world data into rigorous analyses
- Exceptional written communication skills, including the ability to convey technical findings clearly
- A detail-oriented and consistent approach to evaluating complex work
- Comfort receiving feedback and calibrating judgment against established standards
Details
- Pay: $100 to $150 per hour (hourly)
- Commitment: 40 hours per week • remote
- Eligible locations: United States
- Platform: Mercor (weekly payouts via Stripe or Wise)
Submit your application via the link below. Qualified candidates move through Mercor's short AI interview and selection process. Projects can be extended, shortened, or concluded early depending on needs and performance.
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