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Volunteer Machine Learning Jobs in Bend, OR (NOW HIRING)

Volunteer Machine Learning information

See Bend, OR salary details

$8

$20

$35

How much do volunteer machine learning jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for volunteer machine learning in Bend, OR is $20.19, according to ZipRecruiter salary data. Most workers in this role earn between $15.19 and $21.30 per hour, depending on experience, location, and employer.

What is a volunteer machine learning?

A Volunteer Machine Learning job involves contributing to machine learning projects without monetary compensation, often for nonprofits, open-source initiatives, or research. Volunteers may help with data preprocessing, model training, evaluation, or deployment. It’s a great opportunity to gain hands-on experience, collaborate with professionals, and apply ML skills to meaningful causes.

What types of projects or tasks can I expect to work on as a volunteer machine learning?

As a Volunteer Machine Learning contributor, you may work on a wide variety of tasks such as preparing and cleaning datasets, developing or enhancing machine learning models, conducting data analysis, and documenting results for open-source or nonprofit initiatives. Projects can range from building predictive models for social impact organizations to supporting data-driven research or assisting with educational outreach. You’ll typically collaborate remotely with other volunteers, data scientists, and project managers, often using shared code repositories and communication tools. This role provides valuable hands-on experience and networking opportunities within the growing field of machine learning.

What are the key skills and qualifications needed to thrive in the volunteer machine learning position?

To thrive as a Volunteer Machine Learning professional, you need a solid understanding of machine learning concepts, data analysis, and basic programming skills, typically demonstrated through coursework, personal projects, or relevant certifications. Familiarity with tools such as Python, TensorFlow, scikit-learn, and collaborative platforms like GitHub is often expected. Strong communication, collaboration, and adaptability are vital for contributing effectively within diverse volunteer teams. These skills and qualities enable volunteers to make meaningful technical contributions while supporting the goals of nonprofit or research-focused projects.

What cities near Bend, OR are hiring for Volunteer Machine Learning jobs?

Cities near Bend, OR with the most Volunteer Machine Learning job openings:

Infographic showing various Volunteer Machine Learning job openings in Bend, OR as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $41,994 per year, or $20.2 per hour.

Data Scientist (Statistician)

US Department of the Treasury

Bend, OR • On-site

$125K/yr

Full-time

Posted 10 days ago


Key responsibilities

  • Identify, assess, and retrieve structured and unstructured data from multiple sources for data science projects.

  • Clean, transform, and integrate data, resolving issues such as missing values, outliers, and duplicates.

  • Apply data-mining models and statistical methods to analyze data, evaluate results, and support decision-making.


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

311th of 855 rated public administrative organizations


Job description

WHAT IS LARGE BUSINESS AND INTERNATIONAL?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s):
    • LBI - ADCCI - Compliance Planning & Analytics (CP&A), Workload Development & Delivery (WDD). Team will be determined at time of selection.

REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:

  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.


AND
You must also meet the following requirement(s):

  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03 or 04 positions.


For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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