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Data Science Jobs in Bellingham, WA (NOW HIRING)

Data Scientist (US)

Bellingham, WA · On-site

$125K - $135K/yr

Own data science projects end to end -- problem framing, method selection, modeling, validation, and presenting results to the leaders who will act on them. * Ship data science work as certified ...

Own data science projects end to end -- problem framing, method selection, modeling, validation, and presenting results to the leaders who will act on them. * Ship data science work as certified ...

Bachelor's degree in Data Science, Computer Science, or a related field * Minimum of 3-5 years of experience in data management, analytics, or similar, preferably within a marketing environment

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Data Science information

See Bellingham, WA salary details

$39K

$127.6K

$204.2K

How much do data science jobs pay per year?

As of Sep 10, 2026, the average yearly pay for data science 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 data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

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 Data Science jobs in Bellingham, WA?

For Data Science jobs in Bellingham, WA, the most frequently searched job titles are:

What job categories do people searching Data Science jobs in Bellingham, WA look for?

The top searched job categories for Data Science jobs in Bellingham, WA are:

What cities near Bellingham, WA are hiring for Data Science jobs?

Cities near Bellingham, WA with the most Data Science job openings:

Infographic showing various Data Science job openings in Bellingham, WA as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $127,574 per year, or $61.3 per hour.

Data Scientist (US)

Bellingham, WA • On-site

$125K - $135K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

Description:

 About Logos


Logos is a purpose-driven tech company dedicated to building technology solutions that equip the church to grow in the light of the Bible. Our team is committed to increasing biblical literacy and accessibility for every Christian around the world. We do so by delivering value along three fronts: software tools, community collaboration, and rich digital content. Based in Bellingham, Washington, Logos also has operations in Chandler, Arizona and Puebla, Mexico.


About the Role


We're looking for a Data Scientist to join our Analytics team, reporting to the Director of Analytics and Data Science. You'll work as a peer to our Staff Data Scientist, jointly owning the data science function at Logos — predictive modeling, experimentation, and the recommendations work that shapes how hundreds of thousands of customers discover and use our products.

This is a role with real ownership. You will decide how to approach problems, what methods fit, and — just as importantly — what isn't worth doing. We're a lean team inside a company in the middle of a significant data transformation, which means the work is broad and the impact is visible, but it also means we need someone who brings their own judgment rather than waiting for direction.

We're results-driven, not academic. A model or analysis is only good if it measurably reduces churn, increases usage, or drives revenue. Methodological elegance that doesn't move a business metric isn't a win here.


Responsibilities

  • Own data science projects end to end — problem framing, method selection, modeling, validation, and presenting results to the leaders who will act on them.
  • Ship data science work as certified, production-ready data products: models, scores, and features that other teams can trust and build on.
  • Design, run, and interpret experiments, including hypothesis formulation, sizing, and honest reads on inconclusive results.
  • Build and maintain predictive models and analytical pipelines in Python or R, SQL, and dbt on Databricks.
  • Help set the data science roadmap alongside the Staff Data Scientist and the Director — including pushing back when a request won't produce value.
  • Partner with Data Champions, the embedded analysts distributed across our business teams, so that data science output gets adopted rather than just delivered.
  • Work with the Data Platform team to validate data quality and the reliability of upstream data products.
  • Mentor analysts and less experienced team members, and contribute to code review and team standards.
  • Keep documentation and reproducible code current enough that a colleague could pick up your work without you in the room.

Requirements

  • 4–7 years of professional experience in data science, applied statistics, or a closely related quantitative field.
  • A track record of owning projects independently, from ambiguous ask through delivered result, without daily oversight.
  • A results-driven mindset: you judge your own work by measurable business impact — churn, usage, revenue — and you can tell when a model isn't earning its keep.
  • Strong SQL and fluency in Python or R.
  • Solid grounding in statistics and experimental design, including knowing the limits of what a given test can tell you.
  • The judgment to prioritize: deciding what to work on, what to defer, and what to decline.
  • Excellent communication skills, with the ability to explain technical work to non-technical audiences and to hold your position when the data supports it.

Preferred Requirements: 

  • Experience as the only data scientist — or one of very few — on a team, where you had to operate without a technical safety net.
  • Hands-on experience with Databricks and dbt.
  • Exposure to production ML systems, recommendation engines, or MLOps practices.
  • Experience in a subscription or SaaS business, particularly around churn, retention, and usage analytics.
  • Familiarity with a data mesh or distributed analytics operating model.

*Why This Role

Data science at Logos is small, which means your work is not one input among dozens — it is the data science capability of the company. You'll have latitude to shape how the function operates, a Staff Data Scientist to think alongside, and a Director who will back your judgment. As the team and the company's data maturity grow, so does the scope available to you.


Benefits

  • Competitive medical, dental, and vision insurance
  • Company-paid basic life, long-term, and short-term disability
  • Flexible paid time off
  • 10 company-paid holidays per year
  • 4 weeks' paid sabbatical after 10 years of service with an additional stipend
  • Paid maternity and paternity leave policy
  • Health Savings Account and Flexible Spending Account options
  • 401(k) plan (Includes an employer match of up to 4%)
  • Awards and recognition program

The U.S. base annual salary for this full-time position ranges from $125k–$135k. Logos salary ranges are determined by role, position level, and location. The range displayed on each remote job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.


Note: Currently, we are able to hire in every state in the United States except for the District Of Columbia.

Requirements: