Data Scientist RF Signal Processing

Job Summary

Applying data science and machine learning to analyze radio frequency and acoustic signals, the full-time salaried Data Scientist RF Signal Processing will design and develop signal processing pipelines and machine learning models while collaborating with engineering experts in a fully remote environment.

Key responsibilities

• Design and develop signal processing pipelines and machine learning models for RF, acoustic, and time-series sensor data
• Evaluate algorithm performance through objective metrics and subjective measures, integrating with speech recognition engines as necessary
• Perform exploratory data analysis and feature extraction on raw RF and acoustic data to identify patterns and anomalies

Required qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, or a closely related discipline
• 5+ years of professional experience in data science, machine learning, or applied signal processing, particularly with RF and acoustic data
• Hands-on experience with time-series and signal processing techniques, including spectral analysis and filtering
• Proficiency in Python and relevant scientific computing libraries and ML frameworks
• Direct industry experience in Aerospace, Telecommunications, Military/Defense communications, or RF/Electronic Systems