Senior Data Scientist - OEE

Data Science at TRACTIAN

The Data Science team at TRACTIAN focuses on extracting valuable insights from vast amounts of industrial data. Using advanced statistical methods, algorithms, and data visualization techniques, this team transforms raw data into actionable intelligence that drives decision-making across engineering, product development, and operational strategies. The team constantly works on optimizing prediction models, identifying trends, and providing data-driven solutions that directly enhance the company’s operational efficiency and the quality of its products.

What You'll Do

As a Data Scientist – OEE at TRACTIAN, you will work at the intersection of advanced data science and industrial operations. Your mission is to develop cutting-edge algorithms and predictive models to monitor and forecast equipment failures before they occur—optimizing asset reliability and reducing downtime. You will tackle complex challenges involving large-scale time-series data, real-time data processing, and machine learning applications, while collaborating closely with engineers to ensure our solutions remain industry-leading.

Responsibilities

• Work directly with Tractian OEE, our product focused on production monitoring.
• Develop classification and regression models.
• Build ML models to evaluate production efficiency.
• Develop statistical models for machine signal processing.
• Design heuristics to model the behavior of an industrial plant.
• Test and evaluate models for performance, accuracy, and recall.
• Integrate existing data pipelines and models from other products into OEE models.
• Collaborate with engineers to improve data pipelines and enhance model accuracy.
• Build scalable, real-time models for low-latency predictions.
• Create diagnostic tools that enable technicians to make data-driven maintenance decisions.
• Continuously refine models based on real-world performance and feedback.

Requirements

• Bachelor’s degree in Software Engineering, Statistics, Computer Science, or related fields.
• Proven experience as a Data Scientist.
• Advanced knowledge of statistics.
• Expertise in machine learning, time-series analysis, and anomaly detection.
• Proficiency in Python.
• Knowledge of signal processing and industrial sensor data.
• Strong problem-solving skills and ability to work with high-dimensional data.

Bonus Points

• Knowledge of Linear Optimization.
• Industrial domain knowledge (machines, production lines, etc.).
• Knowledge of Bayesian Statistics.
• Experience with Kalman Filtering.
• Knowledge of Markov Chains.