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Valuation analyst Jobs in Granby, QC
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Valuation analyst • granby qc
Remote Senior Finance Specialist - AI Trainer
SuperAnnotateGranby, Quebec, CATechnical Production Analyst Support Analyst
FX INNOVATIONRemote, QuebecSr. Programmer / Analyst
Medavie Blue CrossQuebec, CASpécialiste en réclamations de biens bilingue – sur les lieux
Crawford & CompanyQC, CAAnalyste financier senior / Senior Financial Analyst
Teledyne Digital Imaging, Inc.QC,Bromont,Canada- Richmond Hill, ON (from $ 145,265 to $ 185,250 year)
- North York, ON (from $ 95,000 to $ 146,729 year)
- Regina, SK (from $ 38,187 to $ 146,250 year)
- Barrie, ON (from $ 77,547 to $ 139,132 year)
- Calgary, AB (from $ 127,021 to $ 134,049 year)
- Toronto, ON (from $ 79,385 to $ 133,769 year)
- Old toronto, ON (from $ 79,385 to $ 133,744 year)
- Edmonton, AB (from $ 130,293 to $ 132,564 year)
- London, ON (from $ 126,855 to $ 132,419 year)
- Montreal, QC (from $ 100,000 to $ 131,537 year)
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Remote Senior Finance Specialist - AI Trainer
SuperAnnotateGranby, Quebec, CA- Full-time
- Remote
In this hourly, remote contractor role, you will review AI-generated finance analyses and / or generate expert finance content, evaluating reasoning quality and step-by-step problem-solving while providing precise written feedback. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify methodological or conceptual errors; fact-check financial claims and assumptions; write high-quality explanations and model solutions; and rate and compare multiple responses based on correctness and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your finance expertise directly helps improve the world’s premier AI models by making their financial reasoning more accurate, reliable, and clearly explained.
Key Responsibilities :
- Develop AI Training Content : Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
- Optimize AI Performance : Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
- Ensure Model Integrity : Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
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