This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Data Scientist – RF/Acoustics Signal Processing based in the United States.
This role focuses on applying advanced data science and machine learning techniques to complex RF and acoustic signal environments. The successful candidate will transform high-volume, noisy time-series sensor data into actionable insights, diagnostics, and predictive models. Working fully remotely within the U.S. (excluding NY, CA, and IL), the role sits at the intersection of engineering, physics, and applied AI. You will collaborate closely with domain experts to solve ambiguous, real-world industrial and communications challenges. The position requires strong technical rigor in signal processing, along with the creativity to develop scalable ML solutions. It offers the opportunity to impact critical systems across industrial, telecommunications, and defense-adjacent applications. The environment is highly collaborative, data-driven, and innovation-focused.
Accountabilities:
- Design and develop end-to-end signal processing and machine learning pipelines for RF, acoustic, and time-series sensor data, including techniques such as spectral analysis, beamforming, filtering, wavelet decomposition, and time-frequency analysis.
- Build, evaluate, and optimize ML models for anomaly detection, fault isolation, and predictive diagnostics across complex systems and noisy environments.
- Perform exploratory data analysis, feature engineering, and signal feature extraction on raw sensor data to identify patterns, anomalies, and system behavior.
- Support root cause analysis by interpreting RF and acoustic signals at subsystem, component, and system levels.
- Contribute to full ML lifecycle workflows, including data ingestion, model training, deployment, monitoring, and drift detection in production environments.
- Collaborate with engineering teams and subject matter experts to translate operational challenges into scalable data science solutions.
- Communicate technical findings, model performance, and business impact through clear visualizations, documentation, and presentations.
Requirements:
- Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, or a related technical field.
- 5+ years of professional experience in data science, machine learning, or signal processing, with direct exposure to RF, acoustic, ultrasonic, or communications data.
- Industry experience in domains such as aerospace, telecommunications, defense communications, industrial acoustics, or RF/electronic systems.
- Strong hands-on expertise in time-series and signal processing methods, including spectral analysis, filtering, and feature extraction from sensor data.
- Proficiency in Python and scientific/ML libraries such as NumPy, SciPy, pandas, scikit-learn, PyTorch, or TensorFlow.
- Experience working with RF measurement tools such as spectrum analyzers, network analyzers, signal generators, or oscilloscopes.
- Strong analytical thinking skills with the ability to work in ambiguous or data-limited environments.
- Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
- Preferred: Master’s degree in a relevant technical discipline and experience with radar, sonar, wireless protocols (4G/5G), MLOps tools, cloud platforms, or multimodal data fusion.
Benefits:
- Competitive salary range: $98,837 – $154,546, depending on experience
- Medical, dental, and vision insurance coverage
- Health Savings Account (HSA) with employer contributions
- 401(k) retirement plan with employer match
- Short-term and long-term disability insurance
- Life insurance and accidental death & dismemberment coverage
- Paid Time Off (PTO) and eight paid holidays annually
- Flexible remote work within eligible U.S. locations (excluding NY, CA, and IL)
- Additional statutory benefits as required by applicable law