{"schemaVersion":"jobsearcher.job.v1","id":"00c973c35a929519d858e749","url":"https://jobsearcher.com/jobs/00c973c35a929519d858e749","canonicalUrl":"https://jobsearcher.com/jobs/00c973c35a929519d858e749","title":"Data Scientist - Signal Processing Engineer (Acoustics)","description":"Role Information:\nJob Title: Data Scientist - Signal Processing Engineer- (Acoustics)\nWork Location: Fully remote position, home office\nEmployment Type: Full-time\nEmployment Status: Exempt, salaried\nVisa sponsorship is not available for this position.\nMust reside in the United States.\nWe are not accepting applicants for remote workers in California, Illinois, and New York at this time.\nCompensation:\n$98,837 - $175,000, depending on years of experience\nRole Overview:\nApplies data science and machine learning to the analysis of electrical, vibration, and acoustic signals, transforming raw time-series sensor data into actionable diagnostics and predictive insights for rotating industrial equipment. Partners with engineering and domain experts to design and deploy production-grade signal processing and ML solutions for predictive maintenance across industrial applications. Operates effectively in ambiguous problem spaces where signal quality, environmental noise, and domain constraints require both technical rigor and adaptive thinking.\n\nKey Responsibilities:\nDesign and develop signal processing pipelines and machine learning models that operate on electrical (current/voltage), vibration, and acoustic time-series sensor data, including symmetrical component analysis, matched filtering, wavelet decomposition, and time-frequency analysis techniques.\nEvaluate algorithm performance using both objective metrics and subjective measures, including integration with speech recognition engines where applicable.\nPerform exploratory data analysis, feature engineering, and signal feature extraction on raw electrical, vibration, and acoustic data to surface fault patterns and anomalies.\nAnalyze and interpret signals from electrical asset monitoring systems (motors, generators, pumps) utilizing electrical signature analysis, vibration analysis, and signal processing expertise to support fault isolation and anomaly detection.\nUse cross-sensor asset monitoring data (temperature, speed, load) to characterize and validate signal-derived diagnostics.\nApply data-driven signal processing methods to characterize and isolate faults at the subsystem, component, and machine level, identifying root causes from spectral, electrical, and vibration sensor data in rotating industrial equipment.\nContribute to end-to-end ML workflows including data ingestion, model training, inference, and monitoring for drift and degradation in live environments.\nCollaborate with engineering, product, and domain SMEs to translate operational challenges into well-scoped data science solutions.\nCommunicate findings, model performance, and business value clearly through visualizations, written documentation, and presentations to technical and non-technical stakeholders.\nExplore and evaluate emerging signal processing and AI techniques, recommending production incorporation where appropriate.\nRequired Qualifications:\nBachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Mechanical Engineering, Aerospace Engineering, or a closely related engineering discipline required.\n5+ years of professional experience in data science, machine learning, or applied signal processing, with demonstrated work on electrical, current/voltage, or industrial sensor signal data.\nDirect industry experience in one or more of: Industrial/Rotating Equipment, Power Systems, Electrical Machine Diagnostics, or Condition Monitoring.\nHands-on experience with time-series and signal processing techniques, including spectral analysis, filtering, and feature extraction from raw sensor data.\nProficiency in Python, including scientific computing libraries (NumPy, SciPy, pandas) and ML frameworks (scikit-learn, PyTorch, or TensorFlow).\nFamiliarity with electrical measurement and analysis workflows (e.g., current/voltage waveform capture, power quality analyzers, or equivalent instrumentation).\nStrong analytical and problem-solving skills with the capacity to work through ambiguous or data-sparse problem spaces.\nExcellent written and verbal communication skills; ability to present technical findings to non-technical audiences.\nPreferred Qualifications:\nMaster’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Data Science, or a related field.\nExperience with Electrical Signature Analysis (ESA), Motor Current Signature Analysis (MCSA), or similar electrical machine diagnostic techniques.\nFamiliarity with rotating machinery fault physics (bearing fault frequencies, eccentricity, winding faults, broken rotor bars).\nDemonstrated ability to own an ML model from prototype through production, including monitoring and retraining.\nFamiliarity with array/multi-sensor signal fusion across electrical and vibration domains.\nFamiliarity with cloud platforms (AWS, Azure, GCP) and MLOps tooling (MLflow, Docker, Airflow, CI/CD pipelines).\nExperience with physics-informed modeling approaches.\nActive participation in the broader signal processing or data science community through publications, open-source projects, or conference presentations.\nOther Qualifications:\nSuccessfully pass background check for cybersecurity site access.\nStrong foundation in signal processing theory and application, including experience with electrical, acoustic, or time-series data in a professional setting.\nProficiency in Python for data manipulation, signal processing, and model development (NumPy, SciPy, pandas, scikit-learn, PyTorch or TensorFlow).\nAbility to work with uncertainty and incomplete information; comfortable forming and testing hypotheses when ground truth is limited.\nClear communicator capable of translating technical signal processing and ML findings to non-specialist audiences.\nSelf-directed and effective working remotely across cross-functional teams.\nMust reside in the United States; not accepting applicants in California, Illinois, or New York.\nCybersecurity Role Expectations:\nCandidate will be responsible for reviewing policies and procedures related to cybersecurity and those relevant to the functions of their role.\nCandidate is expected to maintain a cybersecure work environment.\nBenefits:\nPaid Time Off\nMedical, Vision, Dental Insurance\nHealth Savings Account with Employer contributions\n401(k) with Employer match\nShort-term & Long-term Disability Coverage\nAccidental Death & Dismemberment Coverage\nLife Insurance Coverage\nEight paid holidays per year\nAll other benefits required by applicable law\nAlignment with Corporate Values\nAll Cutsforth employees are expected to perform their work in a manner that exhibits understanding and adherence to the Company Mission and Core Attributes of Cutsforth Employees. Employees in management roles must exhibit continual improvement along Cutsforth’s Leadership Traits. Further, each employee must read and adhere to corporate policies and safety protocols.\nLearn more about Cutsforth here, including our Mission & Values: Cutsforth.com/About\nEqual Employment Opportunity Statement:\nCutsforth will not discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, or national origin. Cutsforth will take affirmative action to ensure that applicants are employed, and that employees are treated during employment, without regard to their race, color, religion, sex, sexual orientation, gender identity, or national origin. Such action shall include, but not be limited to the following: Employment, upgrading, demotion, or transfer, recruitment or recruitment advertising; layoff or termination; rates of pay or other forms of compensation; and selection for training, including apprenticeship. Cutsforth agrees to post in conspicuous places, available to employees and applicants for employment, notices to be provided by the provisions of this nondiscrimination clause.\nFor Cutsforth's full Equal Employment Opportunity Policy, click here: EEO Notice to Employees & Applicants\nCalifornia Privacy Notice:\nIf you are a California resident, please review our California Job Applicant Privacy Policy for details regarding the personal information we collect during the hiring process, how we use it, and your rights under the CCPA. By submitting your application, you acknowledge that you have read and understand our privacy practices.\n\nFor Cutsforth's full CCPA Privacy Policy, click here CCPA: California Privacy Notice to Applicants\nWashington State Fair Chance Act:\nCutsforth considers all qualified applicants, including those with criminal histories, in accordance with the Washington State Fair Chance Act. We do not automatically exclude applicants because of a criminal record. Any criminal background check occurs only after a conditional offer of employment, and any resulting decision is based on an individualized assessment of the record's relationship to the specific job.\nLearn more about your rights and our process here: Fair Chance Act\na3odApM0OB","company":"Cutsforth","rawCompany":"cutsforth","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-04T20:38:36.886Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"17-2071.00","title":"Electrical Engineers","slug":"electrical-engineers"}],"industries":[{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Scientist - Signal Processing Engineer (Acoustics)","description":"Role Information:\nJob Title: Data Scientist - Signal Processing Engineer- (Acoustics)\nWork Location: Fully remote position, home office\nEmployment Type: Full-time\nEmployment Status: Exempt, salaried\nVisa sponsorship is not available for this position.\nMust reside in the United States.\nWe are not accepting applicants for remote workers in California, Illinois, and New York at this time.\nCompensation:\n$98,837 - $175,000, depending on years of experience\nRole Overview:\nApplies data science and machine learning to the analysis of electrical, vibration, and acoustic signals, transforming raw time-series sensor data into actionable diagnostics and predictive insights for rotating industrial equipment. Partners with engineering and domain experts to design and deploy production-grade signal processing and ML solutions for predictive maintenance across industrial applications. Operates effectively in ambiguous problem spaces where signal quality, environmental noise, and domain constraints require both technical rigor and adaptive thinking.\n\nKey Responsibilities:\nDesign and develop signal processing pipelines and machine learning models that operate on electrical (current/voltage), vibration, and acoustic time-series sensor data, including symmetrical component analysis, matched filtering, wavelet decomposition, and time-frequency analysis techniques.\nEvaluate algorithm performance using both objective metrics and subjective measures, including integration with speech recognition engines where applicable.\nPerform exploratory data analysis, feature engineering, and signal feature extraction on raw electrical, vibration, and acoustic data to surface fault patterns and anomalies.\nAnalyze and interpret signals from electrical asset monitoring systems (motors, generators, pumps) utilizing electrical signature analysis, vibration analysis, and signal processing expertise to support fault isolation and anomaly detection.\nUse cross-sensor asset monitoring data (temperature, speed, load) to characterize and validate signal-derived diagnostics.\nApply data-driven signal processing methods to characterize and isolate faults at the subsystem, component, and machine level, identifying root causes from spectral, electrical, and vibration sensor data in rotating industrial equipment.\nContribute to end-to-end ML workflows including data ingestion, model training, inference, and monitoring for drift and degradation in live environments.\nCollaborate with engineering, product, and domain SMEs to translate operational challenges into well-scoped data science solutions.\nCommunicate findings, model performance, and business value clearly through visualizations, written documentation, and presentations to technical and non-technical stakeholders.\nExplore and evaluate emerging signal processing and AI techniques, recommending production incorporation where appropriate.\nRequired Qualifications:\nBachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Mechanical Engineering, Aerospace Engineering, or a closely related engineering discipline required.\n5+ years of professional experience in data science, machine learning, or applied signal processing, with demonstrated work on electrical, current/voltage, or industrial sensor signal data.\nDirect industry experience in one or more of: Industrial/Rotating Equipment, Power Systems, Electrical Machine Diagnostics, or Condition Monitoring.\nHands-on experience with time-series and signal processing techniques, including spectral analysis, filtering, and feature extraction from raw sensor data.\nProficiency in Python, including scientific computing libraries (NumPy, SciPy, pandas) and ML frameworks (scikit-learn, PyTorch, or TensorFlow).\nFamiliarity with electrical measurement and analysis workflows (e.g., current/voltage waveform capture, power quality analyzers, or equivalent instrumentation).\nStrong analytical and problem-solving skills with the capacity to work through ambiguous or data-sparse problem spaces.\nExcellent written and verbal communication skills; ability to present technical findings to non-technical audiences.\nPreferred Qualifications:\nMaster’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Data Science, or a related field.\nExperience with Electrical Signature Analysis (ESA), Motor Current Signature Analysis (MCSA), or similar electrical machine diagnostic techniques.\nFamiliarity with rotating machinery fault physics (bearing fault frequencies, eccentricity, winding faults, broken rotor bars).\nDemonstrated ability to own an ML model from prototype through production, including monitoring and retraining.\nFamiliarity with array/multi-sensor signal fusion across electrical and vibration domains.\nFamiliarity with cloud platforms (AWS, Azure, GCP) and MLOps tooling (MLflow, Docker, Airflow, CI/CD pipelines).\nExperience with physics-informed modeling approaches.\nActive participation in the broader signal processing or data science community through publications, open-source projects, or conference presentations.\nOther Qualifications:\nSuccessfully pass background check for cybersecurity site access.\nStrong foundation in signal processing theory and application, including experience with electrical, acoustic, or time-series data in a professional setting.\nProficiency in Python for data manipulation, signal processing, and model development (NumPy, SciPy, pandas, scikit-learn, PyTorch or TensorFlow).\nAbility to work with uncertainty and incomplete information; comfortable forming and testing hypotheses when ground truth is limited.\nClear communicator capable of translating technical signal processing and ML findings to non-specialist audiences.\nSelf-directed and effective working remotely across cross-functional teams.\nMust reside in the United States; not accepting applicants in California, Illinois, or New York.\nCybersecurity Role Expectations:\nCandidate will be responsible for reviewing policies and procedures related to cybersecurity and those relevant to the functions of their role.\nCandidate is expected to maintain a cybersecure work environment.\nBenefits:\nPaid Time Off\nMedical, Vision, Dental Insurance\nHealth Savings Account with Employer contributions\n401(k) with Employer match\nShort-term & Long-term Disability Coverage\nAccidental Death & Dismemberment Coverage\nLife Insurance Coverage\nEight paid holidays per year\nAll other benefits required by applicable law\nAlignment with Corporate Values\nAll Cutsforth employees are expected to perform their work in a manner that exhibits understanding and adherence to the Company Mission and Core Attributes of Cutsforth Employees. Employees in management roles must exhibit continual improvement along Cutsforth’s Leadership Traits. Further, each employee must read and adhere to corporate policies and safety protocols.\nLearn more about Cutsforth here, including our Mission & Values: Cutsforth.com/About\nEqual Employment Opportunity Statement:\nCutsforth will not discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, or national origin. Cutsforth will take affirmative action to ensure that applicants are employed, and that employees are treated during employment, without regard to their race, color, religion, sex, sexual orientation, gender identity, or national origin. Such action shall include, but not be limited to the following: Employment, upgrading, demotion, or transfer, recruitment or recruitment advertising; layoff or termination; rates of pay or other forms of compensation; and selection for training, including apprenticeship. Cutsforth agrees to post in conspicuous places, available to employees and applicants for employment, notices to be provided by the provisions of this nondiscrimination clause.\nFor Cutsforth's full Equal Employment Opportunity Policy, click here: EEO Notice to Employees & Applicants\nCalifornia Privacy Notice:\nIf you are a California resident, please review our California Job Applicant Privacy Policy for details regarding the personal information we collect during the hiring process, how we use it, and your rights under the CCPA. By submitting your application, you acknowledge that you have read and understand our privacy practices.\n\nFor Cutsforth's full CCPA Privacy Policy, click here CCPA: California Privacy Notice to Applicants\nWashington State Fair Chance Act:\nCutsforth considers all qualified applicants, including those with criminal histories, in accordance with the Washington State Fair Chance Act. We do not automatically exclude applicants because of a criminal record. Any criminal background check occurs only after a conditional offer of employment, and any resulting decision is based on an individualized assessment of the record's relationship to the specific job.\nLearn more about your rights and our process here: Fair Chance Act\na3odApM0OB","datePosted":"2026-08-04T20:38:36.886Z","dateModified":"2026-08-04T20:38:36.886Z","hiringOrganization":{"@type":"Organization","name":"Cutsforth","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"00c973c35a929519d858e749"},"url":"https://jobsearcher.com/jobs/00c973c35a929519d858e749"}}