The Role
Apply data science and ML to RF and acoustic time-series: build signal processing pipelines, extract features, develop and deploy models for anomaly detection and fault isolation, collaborate with engineering and domain experts, and monitor production model performance.
Summary Generated by Built In
Role Information:
Key Responsibilities:
- Job Title: Data Scientist — RF/Acoustics Signal Processing
- Work Location: Fully remote position, home office- can NOT be located in NY, CA or IL
- Employment Type: Full-time
- Employment Status: Exempt, salaried
- Visa sponsorship is not available for this position.
- Must reside in the United States.
- We are not accepting applicants for remote workers in California, Illinois, and New York at this time.
- Learn more about Cutsforth here: Cutsforth.com/About
- Read our Mission & Values here: Cutsforth.com/Values
- $98,837 - $154,546, depending on years of experience
Key Responsibilities:
- Design and develop signal processing pipelines and machine learning models that operate on RF, acoustic, and time-series sensor data, including beamforming, BSS, spectral subtraction, matched filtering, wavelet decomposition, and time-frequency analysis techniques.
- Evaluate algorithm performance using both objective metrics and subjective measures, including integration with speech recognition engines where applicable.
- Perform exploratory data analysis, feature engineering, and signal feature extraction on raw demodulated RF and acoustic data to surface patterns and anomalies.
- Analyze and interpret signals from various electrical asset monitoring systems utilizing RF, acoustic, and signal processing expertise to support fault isolation and anomaly detection.
- Use asset monitoring sensor data as measurement to characterize and validate signal data.
- Apply data-driven signal processing methods to characterize and isolate faults at the subsystem, component, and LRU level — identifying root causes from spectral, RF, and acoustic sensor data in complex industrial systems.
- Contribute to end-to-end ML workflows including data ingestion, model training, inference, and monitoring for drift and degradation in live environments.
- Collaborate with engineering, product, and domain SMEs to translate operational challenges into well-scoped data science solutions.
- Communicate findings, model performance, and business value clearly through visualizations, written documentation, and presentations to technical and non-technical stakeholders.
- Explore and evaluate emerging signal processing and AI techniques, recommending production incorporation where appropriate.
- Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, or a closely related engineering discipline required.
- 5+ years of professional experience in data science, machine learning, or applied signal processing, with demonstrated work on RF, acoustic, ultrasonic, or communications signal data.
- Direct industry experience in one or more of: Aerospace, Telecommunications, Military/Defense communications, Industrial Acoustics, or RF/Electronic Systems.
- Hands-on experience with time-series and signal processing techniques, including spectral analysis, filtering, and feature extraction from raw sensor or radio data.
- Proficiency in Python, including scientific computing libraries (NumPy, SciPy, pandas) and ML frameworks (scikit-learn, PyTorch, or TensorFlow).
- Demonstrated use of RF measurement and analysis workflows, including use of spectrum analyzers, network analyzers, signal generators, and oscilloscopes in a professional engineering context.
- Strong analytical and problem-solving skills with the capacity to work through ambiguous or data-sparse problem spaces.
- Excellent written and verbal communication skills; ability to present technical findings to non-technical audiences.
- Knowledge of Electromagnetic Compliance techniques.
- Master’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, Data Science, or a related field.
- Experience with radar sensing, sonar, guided-wave radar, ultrasonic sensing, or capacitive sensing systems.
- Experience working with wireless protocols (4G/LTE, 5G, or military-equivalent).
- Demonstrated ability to own an ML model from prototype through production, including monitoring and retraining.
- Familiarity with beamforming, spatial filtering, or array signal processing in acoustic or RF environments.
- Background in military communications systems, avionics radar, or cellular infrastructure signal analysis.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tooling (MLflow, Docker, Airflow, CI/CD pipelines).
- Experience with multimodal data fusion, edge ML deployment, or physics-informed modeling approaches.
- Active participation in the broader signal processing or data science community through publications, open-source projects, or conference presentations.
- Amateur (Ham) Radio license or comparable hands-on RF communications background.
- Successfully pass background check for cybersecurity site access.
- Strong foundation in signal processing theory and application, including experience with RF, acoustic, or time-series data in a professional setting.
- Proficiency in Python for data manipulation, signal processing, and model development (NumPy, SciPy, pandas, scikit-learn, PyTorch or TensorFlow).
- Ability to work with uncertainty and incomplete information — comfortable forming and testing hypotheses when ground truth is limited.
- Clear communicator capable of translating technical signal processing and ML findings to non-specialist audiences.
- Self-directed and effective working remotely across cross-functional teams.
- Must reside in the United States; not accepting applicants in California, Illinois, or New York.
- Candidate will be responsible for reviewing policies and procedures related to cybersecurity and those relevant to the functions of their role.
- Candidate is expected to maintain a cybersecure work environment.
- Paid Time Off
- Medical, Vision, Dental Insurance
- Health Savings Account with Employer contributions
- 401(k) with Employer match
- Short-term & Long-term Disability Coverage
- Accidental Death & Dismemberment Coverage
- Life Insurance Coverage
- Eight paid holidays per year
- All other benefits required by applicable law
Skills Required
- Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, or closely related discipline
- 5+ years professional experience in data science, machine learning, or applied signal processing with RF, acoustic, ultrasonic, or communications signal data
- Direct industry experience in Aerospace, Telecommunications, Military/Defense communications, Industrial Acoustics, or RF/Electronic Systems
- Hands-on experience with time-series and signal processing techniques (spectral analysis, filtering, feature extraction)
- Proficiency in Python including NumPy, SciPy, pandas and ML frameworks (scikit-learn, PyTorch, or TensorFlow)
- Demonstrated use of RF measurement and analysis workflows (spectrum analyzers, network analyzers, signal generators, oscilloscopes)
- Knowledge of Electromagnetic Compliance techniques
- Strong analytical and problem-solving skills; ability to work in ambiguous, data-sparse problem spaces
- Excellent written and verbal communication skills; present technical findings to non-technical audiences
- Must reside in the United States and cannot be located in California, Illinois, or New York
- Visa sponsorship is not available; candidates must be authorized to work without sponsorship
- Successfully pass background check for cybersecurity site access
- Master's degree in a related field
- Experience with radar, sonar, guided-wave radar, ultrasonic sensing, or capacitive sensing systems
- Experience with wireless protocols (4G/LTE, 5G, or military-equivalent)
- Demonstrated ability to take ML models from prototype to production, including monitoring and retraining
- Familiarity with beamforming, spatial filtering, or array signal processing
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tooling (MLflow, Docker, Airflow, CI/CD)
- Experience with multimodal data fusion, edge ML deployment, or physics-informed modeling
- Active participation in signal processing or data science community (publications, open-source, conferences)
- Amateur (Ham) Radio license or comparable hands-on RF communications background
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The Company
What We Do
Cutsforth™ specializes in developing innovative new technologies and services to enhance plant asset management. We create mechanical, electrical, and software-based solutions to help plants monitor and maintain their critical equipment. Gain real-time insight into your machinery health through asset monitoring solutions and machinery upgrades. Cutsforth's knowledge and commitment to excellence drives our innovative solutions for the changing needs of our customers. Whether a quick response to a critical situation, or a new way of solving an old problem, our commitment to quality ensures our customers receive the best in class products and services---Cutsforth is the Power of Innovation.
