Senior Data Scientist - R&D | System ochrony ptaków

Bioseco is a company combining modern technologies with environmental needs to enable sustainable development of modern industry. They design, implement, and develop solutions using visual analysis, artificial intelligence, and distributed computing technology to support bird safety and protection on airports and wind farms. The company integrates engineering expertise, Internet of Things technology, data analysis, and ecological knowledge.

• Experience in end-to-end data analysis from problem understanding through data preparation to reporting and recommendations.
• Strong practical knowledge of statistics including data description, distributions, dispersion statistics, error types, measurement uncertainty, confidence intervals, hypothesis testing, regression models, GLM, time series analysis, trends, and anomaly detection.
• Proficient in Python with experience in Pandas, NumPy, Matplotlib, Plotly, Scikit-learn, and Statsmodels.
• Skilled in SQL for querying, combining data, and handling large datasets.
• Ability to create clear reports and visualizations to aid problem understanding and decision-making.
• Critical thinking skills to assess data quality and result reliability.
• Self-management skills including work planning, prioritization, and delivering results.
• Effective communication of analytical results to technical and non-technical audiences.
• Good knowledge of English, especially for reading and creating technical documentation.

Nice to have:

• Knowledge of signal processing, including sampling, smoothing, filters, and time signal analysis.
• Experience with data from IoT systems, sensors, monitoring, embedded systems, or field devices.
• Experience with multimedia data such as images, video, or audio.
• Basic practical knowledge of machine learning applications like classification, regression, clustering, and anomaly detection.
• Experience working with environmental, natural, or industrial data.
• Ability to organize analytical code into meaningful project structures using tools like venv and poetry.
• Experience with Jupyter Notebook and JupyterLab.
• Mentoring or leading less experienced analysts.

• Analyze data from environmental monitoring systems, especially from wind farms and airports.
• Work with data from various sources including databases, CSV logs, system reports, and multimedia data.
• Identify analytical problems and select appropriate methods.
• Acquire, clean, combine, and prepare data for analysis.
• Create clear reports for clients and internal diagnostic purposes.
• Prepare data visualizations and interpret results.
• Analyze trends, anomalies, correlations, and system effectiveness.
• Use existing analytical tools and Python scripts, and develop custom ad hoc solutions.
• Support R&D, software, and implementation teams in diagnosing issues and improving the system.
• Formulate conclusions and recommendations based on data.
• Mentor and coordinate the work of Junior Data Analysts.
• Ensure quality, repeatability, and clarity of analyses and reports.