Data Scientist - Predictive Maintenance

Remote
Full Time
Experienced
Role Information:
  • Job Title: Data Scientist - Predictive Maintenance
  • Work Location: Fully remote position, home office
  • 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.
Compensation:
  • $98,837 - $154,546, depending on years of experience

Role Overview:

Applies 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.

Key Responsibilities:
  • Design 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.
  • 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 electrical, vibration, and acoustic data to surface fault patterns and anomalies.
  • Analyze 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.
  • Use cross-sensor asset monitoring data (temperature, speed, load) to characterize and validate signal-derived diagnostics.
  • Apply 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.
  • 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.
Required Qualifications:
  • Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Mechanical 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 electrical, current/voltage, or industrial sensor signal data.
  • Direct industry experience in one or more of: Industrial/Rotating Equipment, Power Systems, Electrical Machine Diagnostics, or Condition Monitoring.
  • Hands-on experience with time-series and signal processing techniques, including spectral analysis, filtering, and feature extraction from raw sensor data.
  • Proficiency in Python, including scientific computing libraries (NumPy, SciPy, pandas) and ML frameworks (scikit-learn, PyTorch, or TensorFlow).
  • Familiarity with electrical measurement and analysis workflows (e.g., current/voltage waveform capture, power quality analyzers, or equivalent instrumentation).
  • 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.
Preferred Qualifications:
  • Master’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Data Science, or a related field.
  • Experience with Electrical Signature Analysis (ESA), Motor Current Signature Analysis (MCSA), or similar electrical machine diagnostic techniques.
  • Familiarity with rotating machinery fault physics (bearing fault frequencies, eccentricity, winding faults, broken rotor bars).
  • Demonstrated ability to own an ML model from prototype through production, including monitoring and retraining.
  • Familiarity with array/multi-sensor signal fusion across electrical and vibration domains.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tooling (MLflow, Docker, Airflow, CI/CD pipelines).
  • Experience with physics-informed modeling approaches.
  • Active participation in the broader signal processing or data science community through publications, open-source projects, or conference presentations.
Other Qualifications:
  • Successfully pass background check for cybersecurity site access.
  • Strong foundation in signal processing theory and application, including experience with electrical, 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.
Cybersecurity Role Expectations:
  • 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.
Benefits:
  • 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

Alignment with Corporate Values

All 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.

Equal Employment Opportunity Statement:

Cutsforth 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.

For Cutsforth's full Equal Employment Opportunity Policy, click here: EEO Notice to Employees & Applicants

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If 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.

For Cutsforth's full CCPA Privacy Policy, click here CCPA: California Privacy Notice to Applicants

Washington State Fair Chance Act:

Cutsforth 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.

Learn more about your rights and our process here: Fair Chance Act

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