As a Data Scientist, you will be responsible for developing, testing, and implementing predictive models and analytical solutions that support data-driven decision-making. You will work closely with Data Engineers and other team members to identify key data sources, clean and process data, and apply statistical analysis and machine learning techniques.
Requirements * Minimum 4+ years of experience in data science * Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field * Strong knowledge of Python and Machine learning libraries ( e.g., TensorFlow, PyTorch) * Deep understanding of SQL and databases with the ability to handle complex queries and optimize database performance * Strong understanding of machine learning algorithms and statistical techniques * Experience with data visualization tools (e.g., Plotly, Matplotlib) * Experience with the end-to-end development cycle, including model development, testing, deployment, and integration into production infrastructure * Excellent presentation/communication skills * English proficiency at Intermediate or higher
As a plus * Experience with NLP for text-based analysis * Familiarity with data engineering tools and processes for data pipeline optimization * Experience with AWS or Google Cloud Platform for managing and processing data in cloud environments * Basic understanding of deploying models using MLOps practices for monitoring and maintenance
Responsibilities * Apply statistical analysis and machine learning techniques to build predictive models and derive insights from data * Experiment with and evaluate different algorithms and techniques to improve model performance * Communicate findings through data visualizations and reports to stakeholders * Deploy machine learning models into production and monitor their performance
We offer * Paid vacation and sick leaves * Competitive salary * Flexible work schedule * Office/hybrid work in Ternopil or opportunity for remote work * Career growth * Corporate celebrating and presents * Coffee, tea, fruits, and cookies in the office * Corporate English courses
