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Surge AI

Delivers high-quality AI training data

AI Programs Analyst - Finance Domain

Program ManagementConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

  • The candidate should have 2–5 years of experience in finance roles such as investment banking, equity research, financial planning and analysis, asset management, risk, audit, or financial consulting.
  • The candidate should have strong analytical skills and be comfortable with financial modeling, data analysis, and interpreting complex financial statements.
  • The candidate should have a track record of managing complex projects in fast-paced environments and be able to navigate ambiguity and balance competing priorities.
  • The candidate should have strong interpersonal skills to influence without authority and communicate financial concepts to technical and non-technical audiences.
  • The candidate should have a deep interest in AI systems.

Responsibilities

  • Lead the delivery of finance-domain AI training, evaluation, and data projects in areas such as financial analysis, equity research, credit assessment, regulatory compliance, and quantitative modeling.
  • Provide finance expertise and design quality frameworks to ensure AI outputs meet the rigor expected by finance professionals.
  • Manage multiple simultaneous projects, set timelines, and coordinate across engineering, operations, and customer teams.
  • Translate domain knowledge into actionable guidance for AI and machine learning teams while interfacing with financial services clients to scope requirements and deliver value.

Desired Qualifications

  • CFA or CPA is a strong plus.
  • Direct AI or machine learning experience is valued but not required.

About the Company

Surge AI

Delivers high-quality AI training data

Surge AI provides high-quality training and evaluation data for AI models. It creates human-annotated datasets, preference data, and reinforcement learning from human feedback (RLHF) to help developers of large language models and other machine learning systems improve accuracy, alignment, and real-world performance, especially for advanced generative AI tasks. The company targets the high end of the data labeling market by prioritizing quality, scalability, and the ability to handle complex, model-critical labeling rather than simple commodity annotations. Its goal is to support better-performing, safer, and more reliable AI systems by delivering data that directly feeds model training and evaluation.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2020

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