Job Details
Senior Data Scientist
Senior Data Scientist at a leading digital ecosystem in Kyrgyzstan. Salary $3,000 – $4,000 net. Responsibilities include ML solutions, RAG systems, data analysis, and A/B testing. Requires 3+ years of experience, Python, ML libraries, big data experience, and English proficiency.
• Design and implementation of end-to-end ML solutions (from research to production) • Development and optimization of RAG systems and LLM services • Data analysis to identify patterns and insights influencing business decisions • A/B testing and model quality evaluation • Fine-tuning and retraining of models • Development of ML/LLM model evaluation and monitoring systems • Integration of predictive and generative models into production in collaboration with MLOps and architects • Participation in the development of the corporate AI platform and CI/CD standards for ML • Documentation of hypotheses, methodologies, and results, preparation of presentations for business • Interaction with products and data owners to formalize tasks
• 3+ years of commercial experience in Data Science / Machine Learning / AI • Strong foundation in statistics, probability, and linear algebra • Deep understanding of ML algorithms, feature engineering, and model evaluation • Proficient Python and ML libraries (pandas, scikit-learn, PyTorch / TensorFlow) • Experience with big data (SQL, Spark, Airflow or similar) • Practical experience with LLMs, RAG, vector databases • Understanding of MLOps practices, Docker, Kubernetes, ML pipelines • Experience in production model deployment • Mentoring skills and experience in cross-functional teams • English language — Upper-Intermediate and above Advantageous: • Experience in telecom, fintech, or banking • Working with cloud ML platforms (AWS, Azure, GCP) • Experience deploying LLMs in a closed environment (on-premise)
• Work in one of the largest digital ecosystems in the country • Participation in the creation of an AI platform at the group of companies level • Strong Data/AI team and mature MLOps processes • Opportunity to influence architecture and technology stack • Competitive salary • Formal employment according to the Labor Code • Professional training and participation in industry conferences
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