ZipRecruiter

Log In

2

Remote Data Scientist Jobs in Spokane, WA (NOW HIRING)

ROI Agency

Data Engineer IV (Remote)

Spokane, WA · Remote

$117K - $140K/yr

ROI Agency is partnered with an established client to fill a remote Data Engineer IV position on a ... Bachelor's degree in CS/IT/Data Science or equivalent experience (Master's preferred). * 10+ years ...

Gravity Jack

Senior iOS Developer

Spokane, WA · Remote

$60.75 - $78.50/hr

Working with 3D assets and 3D scenes Qualifications * BS degree in Computer Science, Engineering ... Experience working with remote data via REST * Experience with third-party libraries and APIs

micro1 AI

Cheminformatics Specialist - Remote

Spokane, WA · On-site +1

$90 - $120/hr

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Corporate Tools

Senior Data Engineer

Post Falls, ID · On-site +1

$150K/yr

This is a remote position, but if you're near one of our local offices, you're welcome to come ... Bachelor's (BA or BS) in computer science, or related field. * 2+ years in a full stack development ...

micro1 AI

Cheminformatics Specialist - Remote

Spokane, WA · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

micro1 AI

AI Trainer - Microbiology Expert

Spokane, WA · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

next page

Showing results 1-20

All JobsData Scientist JobsRemote Data Scientist JobsRemote Data Scientist Jobs in Spokane, WA

Remote Data Scientist information

See Spokane, WA salary details

$37.9K

$124.1K

$198.7K

How much do remote data scientist jobs pay per year?

As of Aug 20, 2026, the average yearly pay for remote data scientist in Spokane, WA is $124,103.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,600.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a remote data scientist?

Remote data scientists are professionals who analyze and interpret complex data while working outside of a traditional office environment, typically from home or another remote location. They use statistical methods, machine learning, and programming to extract insights from data, helping organizations make data-driven decisions. Remote data scientists collaborate with teams virtually, often using tools for communication, data analysis, and project management. This flexible work arrangement allows for talent from anywhere to contribute to companies worldwide, provided they have reliable internet and the necessary technical skills.

What does a remote data scientist do?

Remote data scientists collect, confirm, and interpret data to determine useful information for their employer. Unlike in-house data scientists, remote data scientists work outside the office, either from home or another location with Wi-Fi accessibility. Remote data scientists help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information they get from the records they gather helps businesses make decisions in critical areas, such as product development, sales and marketing techniques, and client retention. You find remote data scientists in many different industries, including pharmaceuticals, manufacturing, and banking.

What key skills and qualifications are 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, usually demonstrated through a relevant degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of data visualization tools are typically required, along with certifications such as Microsoft Certified: Azure Data Scientist Associate or Google Professional Data Engineer. Excellent communication, problem-solving abilities, and self-motivation are critical soft skills for collaborating remotely and delivering insights to stakeholders. These skills are crucial for effectively analyzing data, building predictive models, and driving data-driven decisions in a distributed work environment.

How does a remote data scientist typically collaborate with team members across different time zones?

As a remote data scientist, effective collaboration across time zones often involves leveraging asynchronous communication tools like Slack, project management platforms, and version control systems such as Git. Regular virtual meetings are scheduled to accommodate overlapping hours, and clear documentation becomes crucial for keeping everyone aligned. Proactive communication, sharing progress updates, and setting clear expectations help ensure seamless teamwork despite geographical differences. This structure allows remote data scientists to contribute meaningfully while maintaining flexibility in their work schedules.

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

AspectRemote Data ScientistRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; often requires programming skills in Python or RDegree in Analytics, Business, or related field; may require proficiency in Excel, SQL, and visualization tools
Work EnvironmentResearch-focused, developing models, machine learning, and predictive analyticsData interpretation, reporting, and visualization to support business decisions
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceRetail, marketing, finance, and consulting firms

Remote Data Scientists focus on building models and advanced analytics, while Remote Data Analysts interpret data and create reports. Both roles require strong analytical skills but differ in technical depth and project scope.

More about Remote Data Scientist jobs

What are the most commonly searched types of Data Scientist jobs in Spokane, WA?

The most popular types of Data Scientist jobs in Spokane, WA are:

What are popular job titles related to Remote Data Scientist jobs in Spokane, WA?

For Remote Data Scientist jobs in Spokane, WA, the most frequently searched job titles are:

What job categories do people searching Remote Data Scientist jobs in Spokane, WA look for?

The top searched job categories for Remote Data Scientist jobs in Spokane, WA are:

What cities near Spokane, WA are hiring for Remote Data Scientist jobs?

Cities near Spokane, WA with the most Remote Data Scientist job openings:

Remote Data Scientist jobs near you
Infographic showing various Remote Data Scientist job openings in Spokane, WA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $124,103 per year, or $59.7 per hour.

Data Engineer IV (Remote)

ROI Agency

Spokane, WA • Remote

$117K - $140K/yr

Full-time

Re-posted 28 days ago

Job description

*Due to NERC regulations US Citizenship, Green Card Hold, or Permanent Residency is required for this role.*

ROI Agency is partnered with an established client to fill a remote Data Engineer IV position on a team we have successfully supported for a few years.

This is hands-on engineering position requiring the ability evaluate execution layer code.


Data Engineer IV

Position Summary

The Principal Data Engineer / Architect (Data Engineer IV) is a senior technical leader responsible for defining the enterprise-wide data architecture, platform strategy, and governance standards. This role shapes how data is collected, modeled, processed, secured, and consumed across all applications and business domains, ensuring the long-term scalability, reliability, and performance of the organization’s data ecosystem.

Principal Data Engineers drive large-scale modernization, lakehouse and warehouse architecture, MDM adoption, metadata automation, Delta Lake strategy, multi-cloud integrations, and end-to-end data platform evolution. Operating with full autonomy, this role engages with Directors, senior architects, and cross-functional leaders to guide decisions that impact enterprise systems, analytics, compliance, and technology investments.

This position is both strategic and hands-on when needed—solving the hardest technical problems, creating reusable frameworks, and mentoring senior engineers to elevate overall data engineering maturity across the enterprise.

Essential Functions:

  • Own the long-term design and architecture of the enterprise data ecosystem, including ingestion, storage, modeling, lineage, governance, and analytics layers.
  • Design scalable lakehouse, Delta Lake, and distributed data architectures supporting advanced analytics, operational workflows, and integration across business domains.
  • Lead enterprise-wide modernization projects: warehouse migrations, domain modeling redesigns, governance uplift, streaming adoption, or cross-cloud data integrations.
  • Define and enforce standards for data modeling, lineage, metadata, MDM, quality, security, and compliance across all data teams.
  • Create reusable architectural patterns, frameworks, orchestrations, and platform components adopted across engineering groups.
  • Solve the most complex technical problems, including distributed system bottlenecks, data quality crises, lineage gaps, and multi-domain data reconciliation issues.
  • Guide cost optimization strategy for compute, storage, and orchestration workloads across the data platform.
  • Partner with enterprise architecture, analytics, InfoSec, product, and application engineering to ensure alignment with organizational strategy.·
  • Influence leadership decisions regarding data strategy, platform investments, tooling, and sprint/roadmap priorities.
  • Mentor senior engineers, conduct design reviews, and provide technical leadership across teams to raise the overall engineering bar.

Basic Qualifications:

  • Bachelor’s degree in CS/IT/Data Science or equivalent experience (Master’s preferred).
  • 10+ years experience in data engineering, data architecture, or distributed systems engineering.
  • Proven track record designing and implementing enterprise-scale data platforms with Lakehouse/Delta architectures.
  • Expert-level proficiency with SQL, Spark, Python, Databricks, Delta Lake, Azure Data Factory, and distributed processing.
  • Deep understanding of data modeling (conceptual, logical, physical), governance frameworks, MDM, metadata catalogs, and lineage systems.
  • Experience leading multi-team engineering initiatives and influencing architectural decisions at the leadership level.
  • Strong grounding in security, compliance, data privacy, and regulatory data handling.

Requirements:
None