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