Research Scientist Junior/Junior+
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 12h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 60d ago
The date the source published, not the day we noticed it (2026-09-02). Last seen at its source 4h ago.
We have tracked this listing since 3 Sep 2026 (60 days). The employer's own board has carried it every time we have read it, most recently 4 hours ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
Available worldwide
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 60d ago · last seen 4h ago
The listing
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 or Mexico — 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: Annual leave and paid sick leave as per applicable policies