TL;DR

Data Scientist (Fintech, ML): Designing, developing, and maintaining advanced risk models using machine learning techniques with an accent on hybrid modeling, behavioral analysis, and ML workflow automation. Focus on building scalable data marts, optimizing model performance, and researching new ML architectures like Transformers.

Location: Remote (Fully remote setup). Relocation support is available to our hubs in Armenia, Georgia, Serbia, Portugal, and Spain.

Company

%hirify_global% creates financial freedom in the way people shop, earn and save, offering split payments with no interest or fees to over 40,000 global brands.

What you will do

Design, develop, and maintain risk models using advanced machine learning techniques.
Regularly retrain, monitor, and validate existing models to ensure timely adaptation to changing customer behavior.
Build and manage scalable data marts in BigQuery to support model development and analytical needs.
Contribute to development of internal automation tools (e.g., AutoML components, ML workflows).
Provide data-driven insights through ad-hoc analyses to support product, credit, and operations teams.
Participate in early research and prototyping of new architectures (Transformers, foundation-style embeddings, multimodal models).

Requirements

At least 2 years of experience in roles such as Data Scientist, ML Engineer, or Risk Analyst, with a proven track record of impactful contributions in credit scoring.
Proficiency in Python and experience with key data science and machine learning libraries (e.g., NumPy, Pandas, scikit-learn, CatBoost, XGBoost, LightGBM).
Strong knowledge of PyTorch, with the ability to implement and fine-tune complex machine learning models.
Advanced knowledge of SQL, with the ability to work effectively with large datasets.
Experience in building and deploying end-to-end machine learning solutions that drive measurable business impact.
Hands-on experience with tools like Airflow and Docker for deploying machine learning models into production.
English: C1+ required

Nice to have

Familiarity with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure for scalable data analysis and model deployment.
Proficiency in visualization tools like Tableau or Power BI to effectively communicate insights and support decision-making.
Prior experience working with financial datasets and a strong understanding of risk management principles.

Culture & Benefits

Full-time B2B contract
Fully remote setup
Up to 20% tax allowance
22 paid leave days annually
Stock options (ESOP) in a fast-scaling, pre-IPO company
Flexi benefits you can use for wellness, travel, or learning
Work alongside a high-performing, international engineering team in a global fintech unicorn

Hiring process

Stage 1: Applied
Stage 2: Review
Stage 3: HR call @%hirify_global%
Stage 4: Technical interview @%hirify_global%
Stage 5: Final interview @%hirify_global%
Stage 6: Hired