Data Scientist

• Translate ideas into prototypes and then into production using MLOps best practices. This role extends beyond just modeling in Jupyter notebooks. You will also be responsible for deploying data science solutions, maintaining them, and further developing our solutions. 
• Dive into new technologies in your daily tasks, dedicated hacking days, or sprints. We encourage a culture of active exploration, seeking and applying the latest advancements to improve existing products and create new ones. 
• Take full ownership of features and products from inception to deployment. Your contributions will directly shape the success and evolution of our solutions. 
• Influence our products and foster a collaborative culture through code reviews, pair programming, and knowledge sharing. 

• Proficiency in Python and basic SQL skills 
• Ability to translate ideas into prototypes and then into production, taking ownership of all steps in the product lifecycle. 
• Extensive experience with specialized machine learning (ML) libraries for developing models with clean, scalable, and production-level code 
• Comprehensive knowledge of statistical methods and algorithmic techniques, with the ability to apply them to solve data problem 
• Basic knowledge about cloud platforms such as GCP or AWS 
• Agile mindset with motivation for continuous self and team development in a collaborative work environment. 
• Good English level both spoken and written. 

Nice-to-have: 
Familiarity with LLMs, RAG, and image generation using both commercial and open-source models 
Experience with deploying models on cloud platforms such as GCP or AWS 
Experience with DevOps technologies such as Docker, Kubernetes, and CI/CD 
Experience with cloud infrastructure-as-code (IaC) tools like Terraform or AWS CloudFormation 
Specialized knowledge in a machine learning area such as Graph Theory, Model Optimization, Image Generation, Time Series Analysis, Natural Language Processing (NLP), or Clustering