Data Scientist

Roles &responsabilities

• Process, clean, and transform industrial data (time series).
• Develop predictive and machine learning models for predicting failures and errors in processes and equipment.
• Projecting future production and performance.
• Identifying trends, anomalies, and root causes in data.
• Integrating and analyzing data with tools such as Splunk.
• Deploying scalable solutions in cloud environments.

technical skills:

• Languages: Python (pandas, NumPy, scikit-learn, statsmodels, matplotlib, seaborn), R (optional)
• Machine Learning & Deep Learning: regression, classification, clustering, anomaly detection, forecasting (ARIMA, Prophet, LSTM, neural networks with TensorFlow/PyTorch).
• Databases: SQL (PostgreSQL, SQL Server, MySQL), integration with PI System and Splunk.
• Environments and tools: Jupyter, RStudio, Git.
• Cloud: experience with Azure, AWS, or GCP.