Insurance Data Analyst and AI Specialist

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<strong>About The Job<br><br></strong><strong>Mercor</strong> connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include <strong>Benchmark</strong>, <strong>General Catalyst</strong>, <strong>Peter Thiel</strong>, <strong>Adam D'Angelo</strong>, <strong>Larry Summers</strong>, and <strong>Jack Dorsey</strong>.<br><br><strong>Position:</strong> AI Insurance Data Specialist<br><br><strong>Type:</strong> <strong>Full-time<br><br></strong><strong>Compensation:</strong> <strong>$90,000–$200,000/year<br><br></strong><strong>Location:</strong> <strong>Palo Alto, CA (in-office, 5 days per week) or Remote<br><br></strong><strong>Commitment:</strong> <strong>9:00am–5:30pm PST during training, then local timezone thereafter<br><br></strong><strong>Role Responsibilities<br><br></strong><ul><li>Use proprietary software to label and annotate insurance-related data, ensuring accuracy and consistency for AI model development.</li><li>Curate and deliver high-quality datasets for actuarial, claims, and risk assessment scenarios.</li><li>Collaborate with technical teams to improve annotation workflows and enhance model training tools.</li><li>Identify and solve complex problems in insurance analytics to improve AI performance and accuracy.</li><li>Design and refine efficient data collection and labeling systems for insurance datasets.</li><li>Interpret and execute evolving task guidelines with precision, adaptability, and independent judgment.<br><br></li></ul><strong>Qualifications<br><br></strong><strong>Must-Have<br><br></strong><ul><li>Professional experience in insurance or a related field such as actuarial analysis, risk management, or claims processing.</li><li>Proficiency in both informal and professional English writing and communication.</li><li>Strong analytical, organizational, and problem-solving skills with the ability to work independently.</li><li>Demonstrated ability to interpret complex instructions and ensure data precision.</li><li>Deep interest in the intersection of technology, data, and insurance innovation.<br><br></li></ul><strong>Preferred<br><br></strong><ul><li>Professional certifications such as Associate or Fellow of the Society of Actuaries (ASA/FSA) or Chartered Property Casualty Underwriter (CPCU).</li><li>Experience mentoring or training others in insurance-related practices.</li><li>Familiarity with AI, data annotation tools, or machine learning workflows.</li><li>Comfort with recording short audio or video sessions for data training purposes.<br><br></li></ul><strong>Interview Process<br><br></strong><ul><li>Submit your resume to begin the application process.</li><li>Join a 20-minute initial interview to discuss your background and qualifications.</li><li>If selected to advance, you’ll move on to a technical discussion focused on insurance data, actuarial methods, and annotation experience.</li><li>Complete a short take-home assessment centered on data labeling or analytical problem-solving.</li><li>Conclude with a final conversation with the broader project team.</li><li>The full interview process is typically completed within one week.<br><br></li></ul><strong>Compensation & Legal<br><br></strong><ul><li>Competitive pay ranging from $90,000 to $200,000 annually for U.S.-based professionals, depending on experience and location.</li><li>International pay ranges available upon request.</li><li>Compensation packages may include additional benefits based on location.<br><br></li></ul><strong>Application Process (Takes 20–30 mins to complete)<br><br></strong><ul><li>Submit your resume</li><li>Join a 20-minute initial interview</li><li>Technical discussion on insurance data</li><li>Complete a short take-home assessment</li><li>Final conversation with the project team<br><br></li></ul><strong>Resources & Support<br><br></strong><ul><li>For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome</li><li>For any help or support, reach out to: support@mercor.com<br><br></li></ul><em>PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.<br><br></em>,<br><br>

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