Middle Data Scientist

We are looking for a qualified and experienced Data Scientist to join our team. The role involves conducting experiments with datasets, maintaining data pipelines, training machine learning algorithms, and visualizing results.

• Be a proactive team player
• Collaborate with the team on implementing new features to support growing data needs
• Create, maintain and deploy DS and ML pipelines including data ingestion, preprocessing, feature engineering, model training and inference, analysis and visualization of results
• Create, maintain and deploy LLM-based systems and agentic pipelines including prompt engineering, tool and API integration, memory and context management, inference orchestration and model evaluation
• Share knowledge with other teams on Data Science or project-related topics
• Collaborate with the team on selecting tools and strategies for specific scenarios

• English level Upper-Intermediate+
• Strong mathematical and statistical background, knowledge of tensor calculus
• Strong knowledge of databases such as Postgres, MongoDB, and SQL
• Knowledge of Python and practical experience with Scikit-learn, NumPy, Pandas and Matplotlib
• Experience with gradient boosting algorithms, in particular XGBoost or LightGBM
• Familiarity with LLM orchestration tools such as LangChain, LangGraph
• Experience using or integrating cloud LLM APIs such as OpenAI, Claude, Amazon Bedrock, Vertex AI
• Practical experience with Retrieval-Augmented Generation pipelines and vector databases such as pgvector, FAISS, Weaviate, Pinecone
• Practical experience with prompt engineering techniques, agentic tools and workflows
• Knowledge of at least one framework for building and training neural networks — TensorFlow/Keras or PyTorch, and good understanding of neural network architectures and approaches
• Commercial experience with classical machine learning and deep learning including NLP and CV models such as BERT, ResNet
• Practical skills in building end-to-end ML training pipelines: data loading, preprocessing, training, inference, and working with GitHub/GitLab CI/CD flows
• Experience with Docker or Kubernetes
• Experience as a Data Scientist for over 2 years

• Practical experience with Java and/or JavaScript/TypeScript or willingness to develop in these languages for supporting AI/ML implementations in non-Python tech stacks
• Practical experience with at least one major cloud platform: AWS, Azure or GCP
• Ability to work with Spark and Airflow