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Remote Data Science Jobs in Bellingham, WA (NOW HIRING)

Facility Data Analyst

Bellingham, WA · On-site +1

$56K - $85K/yr

This is a hybrid-remote position that can be based out of the Harris corporate headquarters in St ... What we're looking for in you Bachelor's degree in computer engineering, computer science ...

Full Stack Developer

Ferndale, WA · On-site +1

$121K - $154K/yr

Remote but 2 weeks of mandatory training onsite * Employment Type: Full-time * Employment Status ... data encryption) Preferred Qualifications: * Master's degree in Computer Science, Software ...

Remote but 2 weeks of mandatory training onsite * Employment Type: Full-time * Employment Status ... data encryption) Preferred Qualifications: * Master's degree in Computer Science, Software ...

Senior Azure Cloud Architect

Ferndale, WA · On-site +1

$135K - $168K/yr

Fully remote position, home office * Employment Type: Full-time * Employment Status: Exempt ... Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional ...

Scheduler

Ferndale, WA · On-site +1

$103K - $130K/yr

Work Arrangement: 3 days onsite in Ferndale, WA, 2 days remote *option to work from home Monday and ... Excellent analytical, communication, and leadership skills with ability to present complex data to ...

Remote Data Science information

See Bellingham, WA salary details

$23.5K

$104.4K

$199.3K

How much do remote data science jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote data science in Bellingham, WA is $104,412.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,934.00 and $144,822.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

Can I work remotely in data science?

Yes, data science is a field that often offers remote work opportunities. Many companies hire data scientists to work remotely, requiring skills in programming, data analysis, and tools like Python or R. Remote data science roles typically involve collaboration through online platforms and may require strong communication skills.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Remote data science roles are open to candidates of various ages, and starting a career at 40 is possible with relevant skills in programming, statistics, and machine learning. Many professionals transition into data science later in life by gaining certifications and building portfolios, making age less of a barrier in this field.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

How can I make $100,000 a year working from home?

Remote data scientists can earn $100,000 or more annually by gaining advanced skills in machine learning, programming languages like Python or R, and data visualization tools. Building a strong portfolio, obtaining relevant certifications, and gaining experience in high-demand industries can help achieve this income level while working remotely.
What are the most commonly searched types of Data Science jobs in Bellingham, WA? The most popular types of Data Science jobs in Bellingham, WA are:
What are popular job titles related to Remote Data Science jobs in Bellingham, WA? For Remote Data Science jobs in Bellingham, WA, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Bellingham, WA look for? The top searched job categories for Remote Data Science jobs in Bellingham, WA are:
What cities near Bellingham, WA are hiring for Remote Data Science jobs? Cities near Bellingham, WA with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Bellingham, WA as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $104,412 per year, or $50.2 per hour.
Signal Processing Engineer (RF/Acoustics)

Signal Processing Engineer (RF/Acoustics)

Cutsforth, LLC

Ferndale, WA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Job description

Role Information:
  • Job Title: Signal Processing Engineer (RF/Acoustics)
  • 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.
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
Compensation:
  • $98,837 - $154,546, depending on years of experience
Role Overview:Applies data science and machine learning to the analysis of radio frequency and acoustic signals, transforming raw time-series sensor data into actionable diagnostics and predictive insights. Partners with engineering and domain experts to design and deploy production-grade signal processing and ML solutions across industrial, communications, and defense-adjacent 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 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.
Required Qualifications:
  • 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.
Preferred Qualifications:
  • 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.
Other Qualifications:
  • 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.
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

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