Description:

The Data Science team at TRACTIAN focuses on extracting valuable insights from vast amounts of industrial data.
This team uses advanced statistical methods, algorithms, and data visualization techniques to transform raw data into actionable intelligence.
The goal is to drive decision-making across engineering, product development, and operational strategies.
As a Data Scientist - Predictive Maintenance, you will develop cutting-edge algorithms and predictive models to monitor and predict equipment failures before they occur.
Your work will optimize asset reliability and reduce downtime.
You will face complex challenges involving large-scale time-series data, real-time data processing, and machine learning applications.
Collaboration with engineers and laboratory teams is essential to ensure predictive maintenance solutions remain industry-leading.
Responsibilities include developing predictive maintenance algorithms, analyzing sensor data streams, researching condition monitoring techniques, and building scalable, real-time models.

Requirements:

Expertise in machine learning, time-series analysis, and anomaly detection is required.
Proficiency in Python and common data science and ML libraries such as NumPy, pandas, scikit-learn, and PyTorch is necessary.
A solid understanding of signal processing concepts and hands-on experience with industrial sensor data (e.g., vibration, current, temperature, pressure) is essential.
The ability to read, interpret, and apply insights from academic literature and state-of-the-art research in condition monitoring and fault diagnosis is required.
Experience in designing experiments to validate hypotheses and benchmark models is necessary.
Strong problem-solving skills and the ability to handle noisy, high-dimensional data are required.
Advanced English proficiency is mandatory.

The position offers the opportunity to work at the intersection of advanced data science and industrial operations.
You will be part of a team that is dedicated to optimizing prediction models and enhancing operational efficiency.
There is a focus on continuous learning and staying up to date with the latest academic literature and techniques.
Collaboration with engineers and laboratory teams provides a dynamic work environment.
The role allows for the development of practical solutions that have a direct impact on the company's products and services.

Skills