Data Scientist - Signal Processing Engineer

Job Summary

To support the analysis of electrical, vibration, and acoustic signals, the full-time salaried Data Scientist - Signal Processing Engineer (Acoustics) will design and develop machine learning models and signal processing pipelines remotely, transforming raw sensor data into actionable insights for predictive maintenance in industrial applications.

Key Responsibilities

• Design and develop signal processing pipelines and machine learning models for time-series sensor data analysis
• Perform exploratory data analysis and feature extraction to identify fault patterns and anomalies in electrical and acoustic data
• Collaborate with engineering and domain experts to translate operational challenges into data science solutions

Required Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, or a closely related field
• 5+ years of professional experience in data science, machine learning, or applied signal processing
• Direct industry experience in Industrial/Rotating Equipment, Power Systems, or Condition Monitoring
• Hands-on experience with time-series and signal processing techniques, including spectral analysis and feature extraction
• Proficiency in Python and scientific computing libraries such as NumPy, SciPy, and pandas