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

SOSi

Data Scientist

OR

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 ...

SOSi

Data Scientist

OR · On-site +1

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 ...

All JobsMining Data Analytics JobsMining Data Analytics Jobs in Remote, OR

Mining Data Analytics information

See Remote, OR salary details

$51K

$69.9K

$88.9K

How much do mining data analytics jobs pay per year?

As of Jun 25, 2026, the average yearly pay for mining data analytics in Remote, OR is $69,930.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,900.00 and $84,900.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Mining Data Analytics is a field that values skills and experience over age; many professionals transition into data science later in their careers. Learning programming languages like Python or R and gaining relevant certifications can help regardless of age. Age should not be a barrier to entering data science if you develop the necessary skills and stay current with industry tools.

What is the highest paid job in mining?

The highest paid roles in mining typically include mine managers, senior engineers, and geologists, with salaries often exceeding $150,000 annually. These positions require extensive experience, technical expertise, and often involve overseeing large operations or specialized skills such as data analysis and safety management.

What is the difference between Mining Data Analytics vs Data Analyst?

AspectMining Data AnalyticsData Analyst
Required CredentialsBachelor's in Data Science, Mining Engineering, or related fields; certifications in data analytics or mining softwareBachelor's in Statistics, Data Science, or related fields; certifications in data analysis tools
Work EnvironmentMining sites, data centers, or corporate offices; focus on mineral extraction dataOffice settings, corporate or consulting firms; focus on business data
Employer & Industry UsageMining companies, resource extraction industriesVarious industries including finance, healthcare, retail

Mining Data Analytics and Data Analysts both analyze data, but Mining Data Analytics specializes in mineral extraction data within the mining industry, often requiring industry-specific knowledge and certifications. Data Analysts have a broader scope across multiple industries, focusing on business insights. While both roles involve data interpretation, their environments and applications differ significantly.

Will data mining be replaced by AI?

Data mining in mining data analytics involves extracting useful patterns from large datasets, and AI technologies like machine learning are increasingly used to automate and enhance this process. While AI can perform many tasks traditionally done by data miners, skilled analysts are still needed to interpret results, develop models, and ensure data quality, making complete replacement unlikely in the near term.

What does a data mining analyst do?

A data mining analyst examines large datasets to identify patterns, trends, and relationships that can inform business decisions. They use statistical tools and software such as SQL, Python, or R, and often work in environments requiring strong analytical and problem-solving skills to extract actionable insights.
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Mining Data Analytics jobs near you

Data Scientist

SOSi

OR

Full-time

Posted 10 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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