Python Backend Engineer with Data Science Focus
Our client is a gaming company established to reform the national gaming system. Operating under the principle of exclusivity, its mission is to provide games responsibly, mitigate gambling-related risks, and ensure player protection while preventing fraud.
The project involves developing a highly available, low-latency service that integrates with the front-end, the content management system (CMS), and a recommendation engine.
The outcome will be a REST API capable of delivering a personalized front-end layout configuration to each end customer in real time.
Position – how you’ll contribute
In this role, you will collaborate cross-functionally within the company to define an appropriate CMS structure and support front-end integrations together with the relevant development teams.
The work builds upon an existing PoC implementation. Understanding both the implementation and the underlying concepts may require a basic data science background. As the objective includes defining front-end layout configurations, familiarity with modern front-end development practices will be highly beneficial for effective communication regarding the front-end and CMS system.
The core algorithms are provided by the data science team. Experience with data science-related development will support effective collaboration and a deeper understanding of the recommendation model.
- Strong knowledge of the Python data science stack (NumPy, etc.)
- Experience in Python REST API development using FastAPI or similar frameworks
- Hands-on experience with Redis
- Practical experience with Docker
- Experience working with Google Cloud Platform (GCP)
- Full-stack understanding, including integration between front-end and back-end systems
- Ability and proven experience in building high-availability back-end systems
- Understanding of digital marketplace personalization
- Experience with content management systems (e.g., Drupal)
- Familiarity with front-end development for web and native iOS/Android applications
- Basic understanding of front-end design principles
- Ability to evaluate recommendation system performance, for example through A/B testing using statistical methods
