TL;DR

Data Scientist (Fintech): Designing, developing, and maintaining risk models using advanced machine learning techniques, including hybrid and sequential approaches with an accent on retraining, monitoring, and validating existing models to ensure timely adaptation. Focus on contributing to the development of internal automation tools (e.g., AutoML components, ML workflows) and participating in early research and prototyping of new architectures (Transformers, foundation-style embeddings, multimodal models).

Location: Fully remote

Company

%hirify_global% creates financial freedom in the way people shop, earn and save by reshaping their relationship with money.

What you will do

Design, develop, and maintain risk models using advanced machine learning techniques, including hybrid and sequential approaches.
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.
Fluency in English

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

Hiring process

Stage 4: Technical interview @%hirify_global%
Stage 5: Final interview @%hirify_global%
Stage 6: Hired