Requirements

Expected technologies

Git

Jira

Azure DevOps

Our requirements

• Minimum 5 years of experience as a Data Scientist, including leading machine learning and advanced analytics projects in a business environment
• Proficient in Python and/or R, with practical experience using libraries like scikit-learn, TensorFlow, Keras, PyMC3, XGBoost, or Statsmodels
• Strong knowledge of statistics, probability theory, and time-series analysis, including methods such as Bayesian inference, ARIMA, MCMC, and ANOVA
• Experienced in modern software development workflows and tools like Git, JIRA, Azure DevOps, and familiar with cloud platforms (preferably Azure), big data technologies such as Spark, and ETL pipelines
• Very good command of English (minimum B2), enabling clear communication and collaboration with international teams

Your responsibilities

• Leading end-to-end data science projects—from problem definition and data exploration to model deployment—within a cross-functional, matrix environment
• Designing and implementing advanced statistical models and machine learning algorithms to generate insights from complex biological and operational datasets
• Acting as a strategic data partner for business and R&D teams—translating their needs into actionable analytical solutions that support decision-making across the company
• Presenting findings in a clear, impactful way to both technical and non-technical stakeholders, ensuring insights are understood and applied
• Supporting the development and improvement of the team’s data science infrastructure, including data pipelines, dashboards, and model performance monitoring