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Remote Data Mining Jobs in Remote, OR (NOW HIRING)

SOSi

Data Scientist

OR · On-site +1

Proficient in data mining, statistical modeling, and AI-driven forecasting techniques, with ... Full remote flexibility. Working at SOSi All interested individuals will receive consideration and ...

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Remote Data Mining information

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$46K

$164.9K

$243.3K

How much do remote data mining jobs pay per year?

As of Jun 9, 2026, the average yearly pay for remote data mining in Remote, OR is $164,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,400.00 and $169,800.00 per year, depending on experience, location, and employer.

What is a Remote Data Mining job?

A Remote Data Mining job involves extracting, processing, and analyzing large datasets to uncover patterns, trends, and insights—all while working from a remote location. Professionals in this field use statistical methods, machine learning techniques, and specialized software to transform raw data into actionable insights. These roles are common in industries like finance, marketing, healthcare, and e-commerce, where data-driven decision-making is essential. Remote data miners typically collaborate with teams via digital communication tools and may need proficiency in programming languages like Python or R.

What are the key skills and qualifications needed to thrive in the Remote Data Mining position, and why are they important?

To thrive as a Remote Data Mining professional, you need strong analytical abilities, statistical knowledge, proficiency in programming languages such as Python or R, and a background in computer science, data science, or a related field. Expertise in data mining tools like SQL, RapidMiner, or Weka and familiarity with data visualization platforms are highly valued, and certifications in data analytics can be advantageous. Attention to detail, problem-solving skills, and effective communication are important soft skills for collaborating remotely and presenting insights to stakeholders. These skills enable you to extract valuable patterns and insights from large datasets while working independently and aligning with organizational goals.

What are some common challenges faced by remote data mining professionals, and how can they be addressed?

Remote data mining professionals often encounter challenges such as managing large and complex datasets, ensuring data privacy, and maintaining effective communication with distributed teams. Addressing these challenges typically involves leveraging secure cloud storage solutions, utilizing robust data analysis tools, and adopting clear documentation and regular virtual meetings to stay aligned on project goals. Additionally, building strong time management habits and being proactive in seeking feedback from team members can help remote data miners stay productive and engaged. Most organizations provide access to collaboration platforms and training to help overcome these obstacles, ensuring a supportive and efficient remote work environment.

What are the most commonly searched types of Data Mining jobs in Remote, OR? The most popular types of Data Mining jobs in Remote, OR are:
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What cities near Remote, OR are hiring for Remote Data Mining jobs? Cities near Remote, OR with the most Remote Data Mining job openings:
Remote Data Mining jobs near you

Data Scientist

SOSi

OR • On-site, Remote

Full-time

Posted 24 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.

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