Derivatives & Quant Finance - AI trainer
Required Skills
derivatives expertise
quantitative finance
financial data analysis
ai model training workflows
data annotation
data normalization
spreadsheet evaluation
communication skills
remote team collaboration
adaptability
handling messy datasets
cross-disciplinary collaboration
Job Description
Job Title: Derivatives & Quant Finance - AI Trainer
Job Type: Part-Time
Location: Remote (US, Canada, UK, EU)
Job Summary:
Join our customer's innovative team as a Derivatives & Quant Finance - AI Trainer, where your expertise will help shape the next generation of AI-driven financial tools. You will play a pivotal role in seeding and curating challenging, real-world finance data to improve model learning in a dynamic, finance-adjacent environment.
Key Responsibilities:
- Develop and seed messy, real-world financial data—including derivatives spreadsheets, partial models, and ambiguous artifacts—for AI training.
- Collaborate with a remote team to identify, select, and prepare finance materials for model ingestion.
- Communicate insights and rationale clearly through detailed written and verbal updates.
- Contribute to a broad, evolving data seeding process, where structure emerges iteratively.
- Evaluate and annotate complex financial documents and quantitative inputs for model enhancement.
- Work flexibly across ambiguous flows—sometimes seeding data before rubrics or structures are finalized.
- Help guide the model to reconstruct, normalize, or extend financial data from limited or chaotic sources.
Required Skills and Qualifications:
- Strong background in derivatives and quantitative finance, with hands-on exposure to industry-relevant data.
- Exceptional written and verbal communication skills, especially for complex financial and quantitative concepts.
- Experience handling messy, incomplete, or “in-the-wild” financial datasets.
- Proficiency in evaluating and interpreting spreadsheets, models, and ambiguous financial artifacts.
- Demonstrated ability to work independently and asynchronously within a remote, distributed team.
- Familiarity with AI concepts, data seeding, or AI model training workflows.
- Adaptable and detail-oriented, able to operate effectively in evolving, unstructured project environments.
Preferred Qualifications:
- Prior experience contributing to AI or data science projects in finance or adjacent industries.
- Exposure to tools for data normalization, annotation, or reconstruction of quantitative models.
- Cross-disciplinary collaboration experience in fast-paced, experimental settings.