• Commercial experience in creation and deployment of Python applications, API design, microservice architecture 
• Commercial experience in tests writing (all kinds), CI/CD maintenance
• Experience in ML/AI and/or banking industry is a plus
• Docker, Git, Linux
• SQL
• TDD
• OOP, design patterns
• English B2/C1
  

Opis oferty 

Our product is Machine Learning and AI-based platform used by financial institutions around the world. Acts as an automated compliance analyst that investigates every suspicious transaction, beneficiary and customer in real time. Our poduct helps financial analysts make decisions faster, while improving quality and consistency in the approach to detecting financial crime risk (money laundering, the financing of terrorism, and systemic corruption). Join us and help make the world a safer place!

Modern technology stack: 

• Work methodology: Scrum
• Main technologies: Python 3, Docker, Linux
• Tools used: Python Standard Library, Docker, gRPC, Jupyter Notebooks, Pandas, PySpark, nltk
• Build server: Jenkins, GitHub
• Database: PostgreSQL
• Code reviews: GitHub
• Issue tracking tool: Jira
• Knowledge repository: Confluence, Google Drive
• Operating system: Linux
• Freedom to choose tools: Yes

Job Remuneration: 

• Salary: 14 000 - 22 000 PLN net/month (B2B)
• Employment Type: B2B
• Employee stock options
• Paid days to balance your work and life in a way that suits you best
• Location: Fully remote forever 
• Career growth: Promotion and great development opportunities within the organization

Zakres obowiązków

1. Participate in R&D initiatives – creation of prototypes or proof of concept solutions to extend our products 
2. Develop AML (Anti-Money Laundering) solutions using various NLP and Machine Learning techniques. 
3. Extend the platform to integrate with client systems 
4. Design and build tools, utilities and libraries for Data Science Team 
5. Participate in planning, requirements refinement, and high-level design of the solution 
6. Take end-to-end responsibility for developing and delivering features and components 
7. Write product documentation 
8. Write clean, reusable code 
9. Collaborate closely with teammates (development, data science, project, product)