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AI Sell-Side Finance Data Specialist at Mercor. Location Information: USA. This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.. Role Description. Mercor is partnering with a leading AI research organization to engage professionals with advanced expertise in sell-side finance for a . full-time role . as an . AI Sell-Side Finance Data Specialist . . In this position, you will play a key role in shaping next-generation AI systems by providing high-quality data annotations and expert insights across diverse sell-side finance contexts. Your work will directly contribute to enhancing model accuracy in areas such as:. Trading strategies . Investment banking transactions . Client sales . Regulatory compliance . Operational workflows . Risk assessment . This opportunity is ideal for professionals who combine deep financial domain expertise with analytical rigor and a passion for innovation. You will collaborate closely with technical teams, ensuring that AI models capture the nuance and complexity of real-world sell-side finance environments.. Key Responsibilities. Utilize proprietary software to label and annotate data for projects centered on trading, sales, investment banking, and compliance workflows . Deliver curated, accurate, and high-quality financial datasets for use in AI training . Assist in developing and enhancing efficient annotation tools specifically designed for sell-side finance data . Identify, analyze, and solve complex problems in sell-side domains to enhance model reasoning and reliability . Apply professional judgment to interpret evolving task instructions with precision and consistency . Contribute insights that improve data quality standards and model interpretability . Qualifications. Professional experience in sell-side finance roles such as trader, execution specialist, investment banker, sales professional, compliance officer, operations analyst, or risk manager . Strong command of professional and informal English communication . Excellent analytical, organizational, and interpersonal skills . Proven ability to make sound judgments independently with minimal guidance . Genuine enthusiasm for applying technology and AI to finance . Preferred Qualifications. Advanced finance certifications (Series 7, Series 63, CFA, FRM, or equivalent) . Experience mentoring or training professionals in trading, compliance, or operational finance processes . Familiarity with AI workflows, data annotation, or model training in a technical environment . Comfort with recording short audio or video materials for model evaluation or training purposes . Work Environment. This role may be performed . on-site in Palo Alto, CA . (five days per week) or . fully remote . for qualified candidates with strong self-direction . Initial training follows a 9:00am–5:30pm PST schedule for two weeks, then transitions to your local timezone . Remote employees must use a Chromebook, Mac (macOS 11.0 or later), or Windows 10 or newer computer and maintain reliable smartphone access throughout their work . U.S. applicants must be located outside of Wyoming and Illinois to be considered for this role . Visa sponsorship is not available at this time . Compensation & Benefits. Competitive pay ranging from . $90,000 to $200,000 annually . for U.S.-based professionals, depending on experience and location . Eligible employees may have access to medical benefits, depending on their country of residence . International compensation packages available upon request . Opportunity to work on a high-impact team shaping how AI systems learn, interpret, and apply complex concepts within sell-side finance . Application Process. Submit your resume . Complete a 20-minute interview focused on your experience and expertise . Selected applicants will move through the following steps: . 15-minute phone interview to discuss qualifications and background . Technical deep dive covering your expertise and data annotation experience . A take-home challenge focused on practical problem-solving and analysis . A meet-and-greet with the broader team . The entire process is typically completed within one week of initial contact