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Data Scientist Machine Learning Jobs in Bellingham, WA

Bespoke Labs

Machine Learning Engineer

Bellingham, WA · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Conversica, Inc

Account Executive

Bellingham, WA · On-site

Proven and mature technology: our data science and R&D team has built a platform that seamlessly combines natural language processing and machine learning technologies to carry on autonomous ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Bellingham, WA

Data Scientist Machine Learning information

See Bellingham, WA salary details

$39K

$127.6K

$204.2K

How much do data scientist machine learning jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data scientist machine learning in Bellingham, WA is $127,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $141,400.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Bellingham, WA? The most popular types of Data Scientist Machine Learning jobs in Bellingham, WA are:
What are popular job titles related to Data Scientist Machine Learning jobs in Bellingham, WA? For Data Scientist Machine Learning jobs in Bellingham, WA, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in Bellingham, WA look for? The top searched job categories for Data Scientist Machine Learning jobs in Bellingham, WA are:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Bellingham, WA as of July 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $127,574 per year, or $61.3 per hour.
Data Scientist - Predictive Maintenance

Data Scientist - Predictive Maintenance

Cutsforth, LLC

Ferndale, WA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New

Job description

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.

  • Learn more about Cutsforth here: Cutsforth.com/About
  • Read our Mission & Values here: Cutsforth.com/Values

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

California Privacy Notice:
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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