About the role
Senior Data Scientist Department: Geo Cluster Employment Type: Full Time Location: Kazakhstan Description We are looking for a Senior Data Scientist to join our GeoData team. You will drive architectural decisions, ensure high performance and reliability, mentor engineers, and work closely with product and backend teams to deliver scalable solutions from discovery to release. Key
Responsibilities Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance Translate complex business goals into well-defined data science problems and quantifiable metrics Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance Support the development and growth of other team members through mentorship and participation in onboarding programs Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact Communicate complex technical concepts and findings clearly and concisely to both technical and non-technical stakeholders Skills, Knowledge and Expertise Previous experience in a data science or machine learning role An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus Expert-level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch) Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment Proven experience with event systems, deployment environments, and maintaining production services Familiarity with technologies for streaming, batch, and async data processing. Proficiency in at least one specialized ML domain (e.g., NLP, Computer Vision, Tabular ML, Graph Neural Networks) Strong understanding of software system design principles and the ability to contribute to architectural discussions Experience in experimental design to validate hypotheses and measure the effectiveness of solutions A solid grasp of security, risk, and control concepts in a production environment Conditions &