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Volunteer Machine Learning Jobs in Nevada (NOW HIRING)

Complete certifications for heavy machinery operations as required by the HEaT Department Manager ... LEARNING AND TEACHING * Documentation - Assists in the creation, publishing, and maintenance of ...

Complete certifications for heavy machinery operations as required by the HEaT Department Manager ... LEARNING AND TEACHING * Documentation - Assists in the creation, publishing, and maintenance of ...

Housekeeping Room Attendat

Reno, NV

$14 - $16.75/hr

Career Growth & Learning - 40% of our management hires are internal promotions! * Invest in Your ... Sort laundry, operate machines safely, and handle linen like it's made of gold (or at least 600 ...

Housekeeping Room Attendat

Reno, NV · On-site

$14 - $16.75/hr

Career Growth & Learning - 40% of our management hires are internal promotions! * Invest in Your ... Sort laundry, operate machines safely, and handle linen like it's made of gold (or at least 600 ...

Housekeeping Room Attendat

Reno, NV · On-site

$14 - $16.75/hr

Career Growth & Learning - 40% of our management hires are internal promotions! * Invest in Your ... Sort laundry, operate machines safely, and handle linen like it's made of gold (or at least 600 ...

Housekeeping Room Attendat

Reno, NV · On-site

$14 - $16.75/hr

Career Growth & Learning - 40% of our management hires are internal promotions! * Invest in Your ... Sort laundry, operate machines safely, and handle linen like it's made of gold (or at least 600 ...

... while learning new ones to assist you in your career. The best part is you would be joining a ... You will perform complex machine set up and identify units that fail tests or tolerance levels and ...

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Volunteer Machine Learning information

What are the key skills and qualifications needed to thrive in the Volunteer Machine Learning position, and why are they important?

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 types of projects or tasks can I expect to work on as a Volunteer Machine Learning contributor?

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 is a Volunteer Machine Learning job?

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 are the most commonly searched types of Machine Learning jobs in Nevada? The most popular types of Machine Learning jobs in Nevada are:
What are popular job titles related to Volunteer Machine Learning jobs in Nevada? For Volunteer Machine Learning jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Volunteer Machine Learning jobs in Nevada look for? The top searched job categories for Volunteer Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for Volunteer Machine Learning jobs? Cities in Nevada with the most Volunteer Machine Learning job openings:
Infographic showing various Volunteer Machine Learning job openings in Nevada as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

Reno, NV • On-site

$74K/yr

Other

Posted 5 days ago


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

235th of 691 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS?
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 the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
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 cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

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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