Senior Data Scientist

We are looking for a highly qualified and experienced Senior Data Scientist to join our team. In this position, you will manage the design, implementation, and optimization of advanced data science solutions. You will conduct complex experiments, find actionable insights, develop scalable ML models and support data-driven strategic decision-making.

• Manage the development and implementation of robust Data Science and Machine Learning pipelines: from data acquisition and preprocessing to model training, inference, and visualization of results
• Take ownership of the architecture and optimization of DS/ML pipelines to ensure scalability and efficiency
• Use ML models to create innovative solutions for tasks such as text generation, content automation, etc.
• Collaborate with cross-functional teams to integrate advanced data solutions that meet changing business needs
• Provide recommendations on tools, strategies, and best practices for solving complex Data Science tasks, including those related to LLMs and Generative AI
• Share expertise with the team and other departments, raising the overall technical level of the organization
• Proactively identify opportunities for improving data processes, model performance, and business outcomes.

• English language - Upper-Intermediate+
• Strong mathematical and statistical background, including tensor calculus
• Expertise in working with databases such as Postgres, MongoDB, and SQL
• Proficiency in Python and significant experience with libraries Scikit-learn, NumPy, Pandas, and Matplotlib
• Deep knowledge and experience with gradient boosting algorithms such as XGBoost or LightGBM
• Advanced experience with at least one neural network framework - TensorFlow/Keras or PyTorch, and deep understanding of neural network architectures and optimization techniques
• Proven commercial experience with classic machine learning and deep learning, including NLP and computer vision, such as BERT, ResNet
• Experience applying LLMs and Generative AI technologies, such as GPT or transformer-based architectures, in real use cases
• Significant experience building end-to-end ML pipelines: data ingestion, preprocessing, model training, deployment, inference, as well as managing CI/CD workflows via GitHub/GitLab
• Hands-on experience with Docker or Kubernetes for deployment and scalability
• Commercial experience with cloud platforms such as AWS or Azure.