Data Science Specialist - Fully Remote | Upto $170/hr

About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: Data Science Expert Type: Contract Compensation: $120–$170/hour Location: Remote Role Responsibilities Design precise, task-specific grading criteria for real-world data science deliverables such as analyses, models, dashboards, and experiment readouts. Score AI-generated and human work samples against criteria with detailed written justifications for every score. Apply consistent, evidence-based judgment to ensure scores are reproducible and defensible. Incorporate structured feedback from senior reviewers and iterate quickly on your work. Work independently and asynchronously to meet deadlines while improving AI model performance . Qualifications Must-Have 5+ years of professional data science experience in industry. Background in business operations, product, or growth data science at top-tier technology companies. Deep fluency in experiment design and A/B testing, metric definition, SQL/Python analysis, and communicating findings to executive stakeholders. Exceptionally strong written communication. Detail-oriented, consistent, and comfortable having your judgment reviewed and calibrated against peers. Preferred Prior experience with AI training , evaluation, or human-data projects. Application Process (Takes 20–30 mins to complete) Submit your resume or relevant technical background to get started. Qualified applicants may be asked to complete a brief technical assessment or submit additional information. Resources & Support For details about the interview process and platform information, please check: For any help or support, reach out to: PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity. Originally posted on Himalayas