AI Sell-Side Finance Data Specialist

AI Sell-Side Finance Data Specialist

AI Sell-Side Finance Data Specialist

Remotive

Remotive

Remote

11 hours ago

No application

About

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