ZipRecruiter

Log In

1

Data Science Jobs in Remote, OR (NOW HIRING)

SOSi

Data Scientist

OR · On-site

Bachelor's degree in Data Science, Statistics, Computer Science, or a related field, or; * seven (7) years of equivalent experience in machine learning and predictive modeling. * Proposed personnel ...

SOSi

Data Scientist

OR · On-site +1

Bachelor's degree in Data Science, Statistics, Computer Science, or a related field, or; * seven (7) years of equivalent experience in machine learning and predictive modeling. * Proposed personnel ...

Stillfront

Data Scientist

Myrtle Point, OR · On-site

Create clear dashboards and reports that communicate model results, test findings, and recommendations to stakeholders YOUR BACKSTORY * 2-5 years of professional experience in data science, data ...

SOSi

Senior Data Scientist

OR · On-site +1

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) years of equivalent experience in AI/ML model development and deployment. * Personnel must have ...

SOSi

Senior Data Scientist

OR · On-site

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) years of equivalent experience in AI/ML model development and deployment. * Personnel must have ...

Kynite

Enterprise Data Architect

OR

Coordinate with the Data Science department to identify future needs and requirements * Provide operational support for Management Information Systems (MIS) Qualifications 10+ years of Data Platform ...

Kynite

Enterprise Data Architect

OR · On-site +1

Coordinate with the Data Science department to identify future needs and requirements * Provide operational support for Management Information Systems (MIS) Qualifications 10+ years of Data Platform ...

Team8

Bluespine-Sr. FWA Analyst

OR · On-site +1

Support engineering and data science teams with audit and FWA concepts, data mapping, and defining data requirements * Determine the likelihood of cases being true error/fraud, based on real-life ...

Team8

Bluespine-Director of Customer Success

OR · On-site +1

Team Collaboration: • Work closely with cross-functional teams such as data scientists, project managers, and consultants to deliver cohesive client solutions. • Contribute to team-wide best ...

Under Armour, Inc.

Lead, Enterprise Data Analyst

OR · Remote

$100K - $135K/yr

Work closely with project teams, enterprise developers, systems analysts, data scientists, and architects to deliver solutions aligned with the enterprise-wide data strategy. * Monitor changes in the ...

Atos

Head of AI

OR · On-site +1

This executive role owns practice P&L, builds scalable offerings (GenAI, ML, data science, AI platforms, MLOps), and partners with sales and delivery leaders to expand revenue and customer impact ...

Atos

Head of AI

OR · On-site +1

This executive role owns practice P&L, builds scalable offerings (GenAI, ML, data science, AI platforms, MLOps), and partners with sales and delivery leaders to expand revenue and customer impact ...

next page

Showing results 1-20

All JobsData Science JobsData Science Jobs in Remote, OR

Data Science information

See Remote, OR salary details

$37.5K

$122.6K

$196.3K

How much do data science jobs pay per year?

As of Jun 19, 2026, the average yearly pay for data science in Remote, OR is $122,617.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,400.00 and $135,900.00 per year, depending on experience, location, and employer.

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.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

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.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in programming, statistical analysis, and machine learning remain essential for designing and deploying AI solutions effectively.

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 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.

What jobs are there in data science?

Data science offers a variety of roles including Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst. These positions typically require skills in programming, statistics, and data visualization tools, and may involve working with large datasets, predictive modeling, and data-driven decision making.

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 jobs does a data scientist do?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use programming languages like Python or R, employ statistical techniques, and often work with machine learning algorithms to solve complex problems across various industries.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Remote, OR? The most popular types of Data Science jobs in Remote, OR are:
What are popular job titles related to Data Science jobs in Remote, OR? For Data Science jobs in Remote, OR, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Remote, OR look for? The top searched job categories for Data Science jobs in Remote, OR are:
What cities near Remote, OR are hiring for Data Science jobs? Cities near Remote, OR with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Remote, OR as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 11% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $122,617 per year, or $59 per hour.

Data Scientist

SOSi

OR • On-site

Full-time

Posted 3 days ago

Job description

Company Description

Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.

Job Description

SOSi is seeking a Data Scientist to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.

Essential Job Duties:

  • The contractor shall develop and refine predictive models, conduct exploratory data analysis, and generate AI-driven insights to enhance intelligence and operational planning.
  • The contractor shall integrate customer feedback into model iteration cycles, leveraging Agile development methodologies to maintain responsiveness to mission requirements.
  • The contractor shall submit the Predictive Model Performance Report, documenting key findings, model accuracy metrics, and operational impact assessments.
  • The contractor shall implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements.
  • The contractor shall provide a Rough Order of Magnitude (ROM) Estimate Report before each analytics project, detailing expected Full-Time Equivalent (FTE) hours, compute costs, storage consumption, and infrastructure requirements.
  • The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.
Qualifications
  • Bachelor's degree in Data Science, Statistics, Computer Science, or a related field, or;
    • seven (7) years of equivalent experience in machine learning and predictive modeling. 
  • Proposed personnel possess the knowledge and capability to develop and refine predictive models, analyze large-scale datasets, and document analytic processes.
  • Proficient in data mining, statistical modeling, and AI-driven forecasting techniques, with experience in working with structured and unstructured data sources.
  • Knowledge of data visualization, feature selection, and geospatial analytics is required.
  • Personnel must be capable of integrating data from multiple sources, ensuring model accuracy, and working within an Agile sprint cycle to deliver iterative improvements.
  • Demonstrated experience in exploratory data analysis, feature engineering, and statistical testing. Experience with Python, R, SQL, and data science libraries (e.g., Pandas, NumPy, SciPy) is required.
  • Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure Machine Learning, and in implementing models into operational workflows.

Preferred Qualifications:

  • Desirable but not required certifications include AWS Certified Data Analytics - Specialty, Microsoft Certified: Azure AI Fundamentals, or Certified Data Scientist (CDS).
Additional Information

Work Environment

  • Full remote flexibility.

Working at SOSi

All interested individuals will receive consideration and will not be discriminated against for any reason.

Apply