Fixed Income & Credit Expert

Job Title: Fixed Income & Credit Expert

Job Type: Part-time

Location: Remote (US, Canada, UK, EU)

Job Summary

Join our customer’s team as a Fixed Income & Credit Expert and play a key role in advancing artificial intelligence for real-world finance applications. You will work on a broad, messy data seeding project, leveraging your understanding of fixed income and credit to enhance model performance with in-the-wild finance artifacts.

Key Responsibilities

1. Seed AI models with diverse, unstructured finance data, including real-world spreadsheets and ambiguous inputs.
2. Collaborate with finance-adjacent contributors to collect and curate data for training.
3. Evaluate and normalize partial models and documentation, iteratively enhancing data structure.
4. Guide the structuring of messy data flows, allowing for initial seeding and deferred organization.
5. Engage with written and verbal communication to document process and share insights across the team.
6. Test and review AI outputs for relevance and accuracy within fixed income and credit domains.
7. Support model improvement by reconstructing or extending incomplete or ambiguous financial artifacts.

Required Skills and Qualifications

1. Strong expertise in fixed income and credit markets, with hands-on experience in finance or financial data analysis.
2. Solid understanding of AI fundamentals and training concepts, especially as applied to messy, real-world data.
3. Outstanding written and verbal communication skills, with the ability to explain complex topics clearly.
4. Comfort working with partial information, ambiguous inputs, and evolving project guidelines.
5. Experience handling large, unstructured datasets and converting them into usable formats for AI training.
6. Collaborative mindset with a proactive approach to knowledge sharing and team engagement.
7. Located in or able to work effectively with teams in the US, Canada, UK, or EU time zones.

Preferred Qualifications

1. Prior involvement in AI or machine learning projects within financial services or fintech.
2. Experience with data seeding, annotation, or training of language models in a finance context.
3. Familiarity with the nuances of broad, ambiguous project scopes and iterative workflow design.