Data Scientist

• Help design, build and continuously improve the clients online platform.
  
• Research, suggest and implement new technology solutions following best practices/standards.
  
• Take responsibility for the resiliency and availability of different products.
  
• Be a productive member of the team.
  
  
  
  

We are seeking a highly skilled Data Scientist with a strong foundation in Operations Research to join our team. This role requires experience in optimization, Python development, and the end-to-end deployment of analytics solutions in commercial or enterprise environments.
Key Qualifications:

• Master’s degree in a relevant field with 4+ years of experience in Operations Research roles.
  
• Strong proficiency in Python (object-oriented programming, clean code principles).
  
• Hands-on experience with optimization solvers (Gurobi preferred, also CPLEX or COIN-OR).
  
• Familiarity with at least one SQL dialect (e.g., PostgreSQL, MySQL, MSSQL).
  
• Basic understanding of cloud platforms and tools such as Jira, Git, Docker, and CI/CD pipelines.
  
• Experience with visual debugging tools like VSCode or PyCharm.
  
• Proven track record in developing and deploying production-ready applications.
  
• Ability to explain complex technical concepts to both technical and non-technical audiences.
  
• Proactive, self-driven, and able to work independently.
  
• Bonus: Experience with simulation and data visualization tools.
  
  

• Ability to build and deploy Python-based REST APIs that interact with databases, perform data manipulation, and return results via endpoints.
  
• Strong understanding of coding best practices, including testing for business logic and endpoint functionality.
  
• Ability to justify and communicate design decisions clearly.
  
  

• Engage with stakeholders to gather requirements and provide data-driven solutions.
  
• Analyze business problems and propose optimization-based approaches.
  
• Build, deploy, and monitor optimization models in production.
  
• Maintain and improve existing models and analytics tools.
  
• Perform ad hoc analyses to support business operations.
  
  
  
  

• A challenging, innovating environment.
  
• Opportunities for learning where needed.