You will implement scoring features, policy rules, and strategies for real-time credit decision-making in a high-load production environment. Additionally, you will maintain existing Python services, ensure high test coverage, and rapidly respond to production incidents.
Risks Scoring Risks Scoring is the team responsible for the automated decision-making behind every Plata product. We integrate data from multiple sources, ship scoring models to production, and serve real-time credit decisions under strict SLAs — for credit cards, cash loans, POS lending and debit products across several countries.
Challenges that await you:
Implementation of scoring features, policy rules and strategies that make real-time decisions on clients in production
Maintenance and development of an existing high-load Python service and its data contracts
Ensuring high implementation quality through comprehensive test coverage
Validating every change against real production traffic before it goes live
Rapid incident response: tracing a decision through logs and restoring correct behaviour quickly
What makes you a great fit:
1+ year of Python experience (internship, own projects or commercial work all count)
Solid Python fundamentals: OOP, dataclasses, standard library
Confident with type hints and static type checking
Basic experience with pydantic: declaring models and validating incoming data
Docker and an understanding of containerization
Practical testing experience with pytest: unit and integration tests, parametrized cases, mocking a dependency
Comfortable with Git and working in a team branch/MR flow
Basic SQL and ability to read someone else's code before writing your own
Proactivity: raising blockers early, asking questions instead of guessing, following existing conventions
B1 or higher English level for effective communication with an international team
Your bonus skills:
gRPC / Protobuf
Kubernetes and Helm
CI/CD pipelines, GitLab CI in particular
Kafka, Pub/Sub or any other message broker and event-driven communication
Interest in MLOps and an understanding of how ML models get to production and are kept there
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 date to challenge the status quo of incumbent finances
Our benefits:
Relocation support to one of our hubs — Cyprus, Serbia, or Kazakhstan — with assistance for the employee and their family
Flexible work from one of our offices or remote
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
“I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!”