Senior Data Scientist

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