Data Scientist Talent Network
Mercor · 100% remote · Contract · Posted
- Pay
- $100–150/hr
- Location
- Worldwide
- Languages
- English
- Hours
- Flexible
- Openings
- Not listed
- Level
- Experienced
Summary
Participate in future projects evaluating AI systems' data science work, including designing grading criteria and evaluating outputs.
What you'll do
- Design task-specific grading criteria for data science deliverables
- Evaluate AI-generated or human-created work against established criteria
- Provide detailed written justifications for evaluations and scores
- Apply consistent, evidence-based judgment
- Incorporate structured feedback from senior reviewers
Requirements
- Have 1+ years of professional data science experience
- Have experience at a leading technology, research, or quantitative firm
- Use Python, SQL, statistical modeling, machine learning, experimentation, and causal inference
- Convey technical findings clearly in writing
- Be detail-oriented and consistent in evaluation
Skills
- Python
- SQL
- Statistical Modeling
- Machine Learning
- Experimentation
- Causal Inference
Full description
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
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