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Develop and train self-supervised foundation models for financial data to improve downstream tasks like credit risk and anti-fraud. Manage the end-to-end lifecycle of research projects, from data collection and experimentation to inference optimization and impact evaluation.
We are looking for a Junior Research Scientist to work on foundation models for financial data. Several of them already run in production on bureau, transactional and graph data; your work is to extend that line to new data domains and new downstream tasks — credit risk, acquisition, anti-fraud, LTV forecasting.
We work with Python, PyTorch, MLFlow, AWS, Snowflake and modern AI coding tools such as Claude Code, OpenAI Codex and Cursor.
This is a great opportunity for someone at the beginning of their career and who wants to work on large-scale, technically challenging projects.
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