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Team Tagline
About the role
We are hiring an AI Research Intern to join our AI Science team and work on transaction-sequence foundation models — learned representations of bank statements and transactional data that can be reused across credit decisioning, fraud detection, and behavioral scoring.
This is a research role with a real product line behind it. You will work directly with our AI Science team on an end-to-end research project: literature review, architecture design, training, evaluation, and — where the work proves out — productionization. This is a 12-month placement; strong performers will be offered full-time conversion.
Required Skills
Preferred Skills
Responsibilities
- Survey the state of the art in tabular and sequence foundation models.
- Design self-supervised pre-training objectives suited to the structure of bank statement data.
- Train transformer-based foundation models on Indicina’s proprietary transaction corpus.
- Benchmark learned representations against current production models on credit risk, fraud, and behavioral scoring tasks.
- Carry out research on architecture, sequence length, and tokenization choices.
- Document findings in a technical writeup; contribute to a publication or open-source release where appropriate.
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