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.
Challenges that await you:
Train self-supervised models on discrete sequences to beat the SOTA and achieve business impact in downstream tasks across Plata, such as: credit risk, transaction anti-fraud, acquisition and LTV forecasting
Stay on top of SOTA research, applying the latest NLP and DL techniques to fintech models
Work with large multimodal datasets: tabular, behavioral, transactional, device and network, text, time series, graphs
Optimize the utilization of compute resources for both training and inference
Own and develop solutions end-to-end, from idea to data collection to experiments to training runs to inference optimization to evaluating impact
Perform rigorous evaluations
Write articles and speak at industry conferences
What makes you a great fit:
Education: mathematics, engineering, computer science, artificial intelligence or another strong quantitative field
Strong foundation in machine learning and deep learning, with hands-on experience building and experimenting with models using PyTorch and LLMs
Understanding of dataset design and data mixing for deep learning training
Demonstrated understanding of how to maximize the utilization of compute resources and efficiently perform experiments to validate research ideas
Solid communication skills
High autonomy and ownership
Your bonus skills:
Published research in machine learning or deep learning
Personal projects or startup experience in AI, machine learning or deep learning
Internship experience in research, ML or DL teams
B1 or higher English level for effective communication with an international team
Our ways of working:
Innovative Spirit: A commitment to creativity and groundbreaking solutions
Honest Feedback: valuing open, transparent communication
Supportive Team: a strong, collaborative community
Celebrating Achievements: recognizing our wins together
High-Tech Environment: a team full of smart and revolutionary people who dare to challenge the status quo of incumbent finances
Our benefits:
Relocation support to one of our hubs — Serbia, Georgia, Mexico or Colombia — with assistance for the employee and their family
Flexible work from one of our offices or remotely within time zones from GMT-2 to GMT+5
Healthcare Coverage
Education Budget: Language lessons, professional training and certifications
Wellness Budget: Mental health and fitness activity reimbursements
Vacation policy: 20 days of annual leave and paid sick leave
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