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What You’ll Own:
- Translate customer goals into dataset specifications, taxonomies, rubrics, and acceptance criteria.
- Design training and evaluation datasets across the financial AI surface: QA, filings, credit, fraud, compliance.
- Evaluate agentic and workflow-integrated financial AI systems for tool use, retrieval, and safety controls.
You’ll Thrive in This Role If You Have:
- 5+ years data science experience with at least 2+ years in financial services or fintech.
- Real working knowledge of financial data and workflows: statements, SEC filings, transaction data.
- Hands-on experience designing datasets for ML, including annotation guidelines and quality thresholds.
About Innodata:
- Innodata partners with foundation model labs, banks, asset managers, and fintechs building AI for financial workflows.
- The role is part of a pod with Technical Solutions Architects, Applied Research Scientists, and AI/ML Research Engineers.
- The company values domain-valid, statistically defensible, compliant, and auditable data for high-stakes AI applications.
Innodata
Innodata is a global data engineering company that enables the responsible advancement of artificial intelligence by providing data, evaluation frameworks, and human expertise. With over 36 years of experience, the company delivers high-quality data and solutions for Generative AI builders and adopters.