Manufacturing Data Scientist: Time-Series ML for ME Systems

Versigent; Lisboa; Presencial; EUR 42.000 - 62.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Private health care

Learning and development opportunities

Opportunities to give back to the社区

Descripción de la vacante

Versigent is seeking a Data Scientist to analyze manufacturing data across processes like Ultrasonic welding, Torque machines, and ROB. You will uncover insights, build time-series models, and work with management to drive value.

Proficiency in Python, ML fundamentals, and data visualization is essential. The role focuses on preprocessing, feature engineering, model implementation, and clear communication of results to stakeholders.

Formación

• Master's degree preferred in a relevant field.
• 0–2 years in a relevant project.
• Strong foundation in statistics and ML.
• Fluent in English, both written and spoken.

Responsabilidades

• Analyze historical data to identify patterns, trends, and insights and compare Statistical Process Control (SPC).
• Preprocess and clean data for machine learning applications
• Create effective feature engineering pipelines for time series data
• Validate data quality and handle missing or anomalous data
• Visualize data and results to communicate findings effectively

Conocimientos

Machine Learning Fundamentals

Data Visualization

Python

Cross-functional collaboration

Educación

Master’s degree (preferred) in Data Science, CS, Math, IT, or Engineering

Herramientas

Scikit-Learn

Streamlit

Seaborn

Numpy

Pandas

SQL

Plotly

StatsModels

Python

Descripción del empleo

Versigent is seeking a Data Scientist to analyze manufacturing data across processes like Ultrasonic welding, Torque machines, and ROB. You will uncover insights, build time-series models, and work with management to drive value.

Proficiency in Python, ML fundamentals, and data visualization is essential. The role focuses on preprocessing, feature engineering, model implementation, and clear communication of results to stakeholders.