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

ROI Agency

Data Engineer IV (Remote)

Spokane, WA · Remote

$115K - $139K/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 ...

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

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.

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Remote Data Science information

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.

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.

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).

Can I work remotely as a remote data scientist?

Yes, many remote data scientist positions are available, allowing professionals to work from anywhere with a reliable internet connection. These roles often require skills in programming, data analysis, and familiarity with tools like Python, R, or SQL, and may involve collaboration through online platforms. Remote work arrangements are common in the data science field, especially with the increasing adoption of cloud-based tools and flexible schedules.

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.

More about Remote Data Science jobs
What are the most commonly searched types of Data Science jobs in Spokane, WA? The most popular types of Data Science jobs in Spokane, WA are:
What are popular job titles related to Remote Data Science jobs in Spokane, WA? For Remote Data Science jobs in Spokane, WA, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Spokane, WA look for? The top searched job categories for Remote Data Science jobs in Spokane, WA are:
What cities near Spokane, WA are hiring for Remote Data Science jobs? Cities near Spokane, WA with the most Remote Data Science job openings:
Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Spokane, WA as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 18% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Engineer IV (Remote)

ROI Agency

Spokane, WA • Remote

$115K - $139K/yr

Full-time

Re-posted 12 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.

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