Research Scientist Junior/Junior+

Plata Card; Deutschland; Hybrid; EUR 42.000 - 54.000; Vollzeit

Benefits dieser Stelle

Relocation support

Flexible work

Healthcare coverage

Education budget

Wellness budget

Vacation policy

Zusammenfassung

Plata Card is looking for a Junior Research Scientist to work on foundation models for financial data. You will extend production models across bureau, transactional and graph data to novel domains and downstream tasks like credit risk, acquisition, anti-fraud and LTV forecasting.

You will use Python, PyTorch, MLFlow, AWS, Snowflake and modern AI tools. This is ideal for someone early in their career who wants to tackle large-scale projects and own solutions end-to-end.

Qualifikationen

• Strong foundation in ML and DL with PyTorch and LLMs.
• Quantitative degree in a relevant field.

Aufgaben

• Develop and train self-supervised models on diverse data across domains.
• Evaluate models rigorously and report business impact.
• Stay updated on SOTA NLP/DL techniques for fintech.
• Work with large multimodal datasets (tabular, transactional, graphs).
• Own end-to-end solutions from data collection to deployment.

Kenntnisse

PyTorch & LLMs

Python

Machine learning fundamentals

Data design & dataset mixing

Compute resource optimization

Autonomy & ownership

Strong communication

Ausbildung

Strong quantitative background (Math, Engineering, CS, AI)

Tools

MLFlow

Claude Code/OpenAI Codex

Cursor

AWS

Snowflake

Jobbeschreibung

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