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Annotation Finance Jobs in Seattle, WA (NOW HIRING)

YO AI Labs

AI Finance Expert - Remote

Seattle, WA · Remote

$100 - $200/hr

AI Finance Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

YO AI Labs

AI Finance Expert - Remote

Seattle, WA · Remote

$100 - $200/hr

AI Finance Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

LVT

Staff Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Named one of the Financial Times' Fastest Growing Companies 2025 and #10 on the Inc. 5000 Rocky ... Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ...

LVT

Staff Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Named one of the Financial Times' Fastest Growing Companies 2025 and #10 on the Inc. 5000 Rocky ... Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ...

Handshake

AI Red Teamer (LLM Generalist)

Seattle, WA · On-site

... with structured data annotation and rubric-based scoring • Prior work in trust and safety ... finance, etc.) Company : Handshake is a college career network that helps students and recent ...

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Showing results 1-20

All JobsAnnotation Finance JobsAnnotation Finance Jobs in Seattle, WA

Annotation Finance information

See Seattle, WA salary details

$23.9K

$60.8K

$106.4K

How much do annotation finance jobs pay per year?

As of Aug 20, 2026, the average yearly pay for annotation finance in Seattle, WA is $60,782.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,800.00 and $68,300.00 per year, depending on experience, location, and employer.

What is an annotation finance job?

An Annotation Finance job typically involves labeling and categorizing financial data to train machine learning models used in fintech applications, such as fraud detection, risk assessment, and financial forecasting. Professionals in this role review and annotate various financial documents, transactions, or datasets to ensure the accuracy and quality of the training data. Attention to detail and a good understanding of financial terminology are important for this position. Annotation Finance specialists may work for financial institutions, technology companies, or data labeling firms. Their contributions are crucial for developing reliable AI systems in the finance sector.

What are common challenges faced by professionals working in annotation finance, and how can they be addressed?

Professionals in Annotation Finance often face challenges related to maintaining high data accuracy and consistency, especially when working with large volumes of financial documents or transactions. Ensuring compliance with evolving regulatory standards and managing sensitive financial information securely are also key concerns. To address these challenges, it's important to stay updated on industry best practices, utilize robust annotation tools, and communicate closely with team members and compliance officers. Regular training and adopting quality assurance protocols can further enhance data reliability and workflow efficiency.

What are the key skills and qualifications needed to thrive as an annotation finance specialist, and why are they important?

To thrive as an Annotation Finance Specialist, you need a solid understanding of financial concepts, data analysis, and attention to detail, typically supported by a degree in finance, accounting, or a related field. Familiarity with data annotation tools, financial modeling software, and spreadsheet applications like Excel is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex data and collaborate with stakeholders. These skills ensure accurate data labeling and analysis, which are critical for driving informed financial decisions and supporting AI or machine learning initiatives in the finance sector.

What is the difference between Annotation Finance vs Data Analyst?

AspectAnnotation Finance
Primary RoleAnnotating financial data for machine learning models in finance
Required SkillsFinancial knowledge, data annotation, attention to detail
Work EnvironmentData labeling teams, finance tech companies
CertificationsBasic financial certifications may help, but not mandatory

Annotation Finance focuses on labeling financial data for AI applications, requiring financial understanding and data annotation skills. Data Analysts analyze and interpret data to inform business decisions, often involving data cleaning and reporting. While both roles work with data, Annotation Finance is specialized in preparing data for machine learning, whereas Data Analysts focus on data analysis and insights.

What are popular job titles related to Annotation Finance jobs in Seattle, WA?

For Annotation Finance jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Annotation Finance jobs in Seattle, WA look for?

The top searched job categories for Annotation Finance jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Annotation Finance jobs?

Cities near Seattle, WA with the most Annotation Finance job openings:

Annotation Finance jobs near you
Infographic showing various Annotation Finance job openings in Seattle, WA as of August 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $60,782 per year, or $29.2 per hour.

AI Finance Expert - Remote

YO AI Labs

Seattle, WA • Remote

$100 - $200/hr

Part-time

Posted 9 days ago

Job description

Job Title: AI Finance Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Finance Domain Experts to contribute their financial expertise to an innovative project at the intersection of finance and artificial intelligence. In this role, you will help improve next-generation AI systems by reviewing, evaluating, and refining AI-generated financial content. No prior AI experience is required—your financial expertise, analytical skills, and professional judgment are what matter most.

Key Responsibilities

  • Analyze, review, and edit AI-generated financial content for accuracy, clarity, and relevance.

  • Develop, refine, and evaluate prompts related to financial analysis, valuation, and investment decision-making.

  • Assess and annotate financial data, reports, and AI-generated outputs using structured evaluation criteria.

  • Author and review investment memos, due diligence reports, research summaries, and technical documentation.

  • Evaluate AI outputs for logical consistency, factual accuracy, and adherence to professional financial standards.

  • Conduct independent research and fact-checking to validate financial information.

  • Provide detailed feedback to improve AI model performance and financial reasoning.

Required Skills

  • Critical Thinking

  • Analytical Reasoning

  • Quality Assurance

  • Prompt Engineering

  • AI Output Evaluation

  • Financial Analysis

  • Technical & Report Writing

  • Business Communication

  • Content Review & Editing

  • Fact Checking

  • Data Interpretation

  • Data Annotation

  • Problem-Solving

  • Independent Research

  • Attention to Detail

Preferred Qualifications

  • Minimum 3 years of experience in private equity, venture capital, investment banking, equity research, corporate development, investment management, or strategic finance.

  • Experience preparing investment memos, valuation analyses, financial models, due diligence reports, or market research.

  • Strong analytical, critical thinking, and problem-solving skills.

  • Excellent written communication and professional editing abilities.

  • Experience with prompt authoring, AI output evaluation, data annotation, or content review is a plus.

  • Master's, MBA, JD, PhD, or another advanced degree is preferred.

  • Commitment to producing high-quality, accurate, and well-documented work.