Finance AI Data Trainer - Phase 2

Finance AI Data Trainer - Phase 2 - 15 Openings - 12/15/2025 (15 openings – Fully Remote, payment via Deel or Stripe) About Finstock, Inc. Finstock is a Hong Kong–based fintech that leverages AI-driven analytics to support investors across U.S. equities, forex and crypto markets. Following a successful beta phase, the firm is expanding its data-training capabilities to accelerate model performance. How to Apply You can apply normally through Indeed, then message us directly on LinkedIn with the content ‘Finance AI Data Trainer - Phase 2 - [Your name]’. We’ll check your LinkedIn profile to verify the authenticity of the candidate, this is a mandatory step. Also, we’d appreciate it if you follow our company LinkedIn page to get the latest updates on upcoming positions Our Linkedin Company page: https://www.linkedin.com/company/finstockinc/ Project Snapshot Engagement length: ~3 months Weekly commitment: 20-40 hours (flexible schedule) Compensation: USD 20 / hour (up to USD 30 / hour for candidates with advanced degrees and deep domain expertise) Payment method: All invoices settled through the Deel contractor platform for global compliance and fast payouts (or Stripe). Role Overview As a Finance AI Data Trainer you will curate, annotate and validate high-quality financial data that powers Finstock’s next-generation models. Your primary focus will be on U.S. GAAP- and IFRS-compliant corporate disclosures, market micro-structure data and FX commentary. You’ll collaborate with quants, machine-learning engineers and fellow subject-matter experts to ensure every data point is accurate, context-rich and model-ready. Key Responsibilities Identify, label and QA-check financial text and numerical datasets related to U.S. equities and global FX. Map GAAP and IFRS concepts (revenue recognition, impairment, hedge accounting, etc.) to machine-readable ontologies. Create annotation guidelines and mentor junior annotators to maintain consistency. Perform targeted data audits and error-analysis feedback loops to improve model precision. Liaise with engineering teams to integrate newly curated datasets into training pipelines. Document edge cases, ambiguities and best practices for continual process refinement. Required Qualifications Bachelor’s degree in Finance, Accounting, Economics, Data Science or a closely related field. 2+ years of experience at a global financial institution (investment bank, asset manager, Big 4 audit, rating agency, etc.). Working knowledge of both U.S. GAAP and IFRS reporting standards. Familiarity with capital-markets data (10-K/10-Q, earnings call transcripts, FX market commentary). Proficient written English; able to summarise complex accounting treatments succinctly. Reliable internet connection and ability to self-manage in a fully remote setting. Preferred (Nice-to-Have) Professional certifications such as ACCA, CFA, CPA or FRM. Experience with annotation tools (Prodigy, Labelbox), SQL or Python for data wrangling. Prior work on NLP/LLM data projects or model evaluation. Advanced degree (MSc, MBA, PhD) in a relevant discipline. What We Offer Flexible hours and location independence. Competitive hourly rate with performance-based upside. Access to Finstock research resources and proprietary analytics. Opportunity to influence AI products used by thousands of traders worldwide. Seamless invoicing and prompt payments via Deel or Stripe, eliminating cross-border complexities. Job Type: Contract Pay: $20.00 - $30.00 per hour Benefits: Flexible schedule Application Question(s): Have you ever been terminated or asked to resign from any previous employment? Do you have any objections if we conduct a background check as part of our hiring process? (Required) Education: Bachelor's (Preferred) Experience: Investment Banking: 2 years (Preferred) Data Annotator: 1 year (Preferred) Accountant: 2 years (Preferred) License/Certification: CFA Charterholder (Preferred) Work Location: Remote