Data Scientist (Remote | $45 –$100/hr)

Remote, USA Full-time
Data Science Tutor (Full Time) Hourly Contract | Remote US | $45 –$100 per hour 1. Role Overview Mercor is partnering with a leading AI research organization to engage experienced Data Science professionals in a full-time, high-impact project focused on training and refining next-generation AI systems. As an AI Tutor – Data Science Specialist, you will play a vital role in improving the performance, reasoning, and analytical depth of large language models (LLMs) by providing high-quality data annotations, structured feedback, and expert insights across quantitative domains. You’ll collaborate with cross-functional teams to design new AI training tasks, evaluate model outputs, and identify challenging data science problems that can enhance model comprehension and technical accuracy. This role is ideal for professionals who combine analytical rigor, curiosity, and technical expertise with a passion for advancing AI technology. 2. Key Responsibilities • Use proprietary tools to label, annotate, and evaluate AI-generated outputs related to data science, modeling, and analytics. • Deliver curated, high-quality datasets that enhance model understanding and reasoning across statistical and computational concepts. • Collaborate with AI research teams to design, test, and refine AI training workflows. • Provide expert input on the development and optimization of annotation tools and processes. • Apply critical thinking to analyze and interpret evolving task guidelines. • Contribute domain knowledge to research-driven initiatives aimed at improving AI reliability and interpretability. 3. Ideal Qualifications • Master’s degree or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or related fields. • Alternatively, recognition from a global quantitative competition such as the International Mathematical Olympiad (IMO) or an equivalent. • Proficiency in both informal and professional English communication. • Strong ability to research and cross-verify technical or academic information. • Excellent analytical, organizational, and communication skills. • Ability to work independently and apply sound judgment in complex problem-solving. • Deep passion for AI innovation, data modeling, and quantitative reasoning. 4. Preferred Qualifications • Publication record in a peer-reviewed journal or recognized research outlet. • Prior experience as an AI Tutor, data annotator, or research contributor. • Background in teaching, tutoring, or academic instruction. • Experience in technical writing, documentation, or journalism. • Professional background as a Data Scientist, Statistician, or Researcher in applied quantitative domains. 5. More About the Opportunity • Location: Remote (US-based) or in-person in Palo Alto, CA (in-office requires 5 days/week). • Schedule: 9:00 AM–5:30 PM PST for the first two weeks; afterward, aligned with your local timezone. • Technical Requirements: • Chromebook, Mac (macOS 11+), or Windows 10+ device. • Reliable smartphone access. • Stable high-speed internet connection with camera and microphone. • Eligibility: U.S. applicants must reside outside of Wyoming and Illinois. • Visa Sponsorship: Not available. 6. Compensation & Contract Terms • Hourly Rate: $45 –$100 USD/hour, depending on experience, expertise, and location. • Classification: Independent Contractor. • International Pay Rates: Available upon request. • Payments issued regularly for completed work. • Hourly compensation is part of a broader performance-based rewards structure; benefits vary by country. 7. Application Process • Submit your resume or CV to begin the process. • Complete a brief screening interview. • If selected, proceed to: • A technical deep-dive on your data science and annotation experience. • A take-home challenge focused on applied data labeling or model evaluation. • A team meet-and-greet with project collaborators. ⚡ PS: Mercor reviews applications daily. Please complete your interview and onboarding steps to be considered for this opportunity. ⚡ Apply tot his job
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