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Volunteer Data Scientist Machine Learning Jobs (NOW HIRING)

Trimble

Machine Learning Data Scientist

Westminster, CO · On-site

$122K - $165K/yr

Essential Skills & Experience * 5+ years of expertise in data science or engineering, specifically building and deploying predictive machine learning models. * Proficiency in Python and SQL for data ...

Judge Group, Inc.

Data Scientist/ ML engineer

Irving, TX · Hybrid

$68 - $73/hr

Data Scientist / Machine Learning Engineer, GenAI We are not accepting C2C or 1099 arrangements. Location: Charlotte, NC or Irving, TX Work Model: Hybrid (3 days onsite per week) Duration: 12-month ...

Koantek

Data Scientist

Chandler, AZ · On-site

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

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Volunteer Data Scientist Machine Learning information

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$37.5K

$122.7K

$196.5K

How much do volunteer data scientist machine learning jobs pay per year?

As of Jun 21, 2026, the average yearly pay for volunteer data scientist machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Volunteer Data Scientist (Machine Learning), and why are they important?

To thrive as a Volunteer Data Scientist (Machine Learning), you need proficiency in statistics, data analysis, programming (Python or R), and a foundational understanding of machine learning algorithms, often supported by a relevant degree or online certifications. Familiarity with tools like scikit-learn, TensorFlow, Jupyter Notebooks, and data visualization platforms is typically required. Strong problem-solving abilities, teamwork, and effective communication are crucial soft skills for translating complex data insights to non-technical stakeholders. These skills and qualities are essential to effectively contribute value, support decision-making, and drive impact in resource-limited volunteer environments.

Is 30 too late for data science?

For a volunteer data scientist or those pursuing a career in data science, starting at age 30 is not too late. Many professionals transition into data science later in life by acquiring relevant skills such as programming, statistics, and machine learning through online courses or certifications, and they can build a successful career regardless of age.

Can I get a data scientist job with no experience?

Entry-level data scientist positions, including those involving machine learning, often require some knowledge of programming, statistics, and data analysis tools. While prior experience is preferred, candidates can improve their chances by completing relevant coursework, certifications, or projects to demonstrate skills. Employers may consider motivated candidates with strong foundational skills and a willingness to learn on the job.

How do Volunteer Data Scientist Machine Learning roles typically collaborate with other team members or departments?

As a Volunteer Data Scientist specializing in Machine Learning, you will often work closely with cross-functional teams such as project managers, software engineers, and subject matter experts. Effective collaboration is essential, as you may need to clarify project goals, source and preprocess data, or translate complex findings for non-technical stakeholders. Regular meetings and open communication help ensure that your machine learning solutions are aligned with the organization's mission and that your insights are actionable. This collaborative environment provides valuable experience working in diverse teams and often leads to impactful, real-world applications of your technical skills.

What is the difference between Volunteer Data Scientist Machine Learning vs Volunteer Data Analyst?

AspectVolunteer Data Scientist Machine LearningVolunteer Data Analyst
Required CredentialsKnowledge of machine learning algorithms, programming skills (Python, R), basic statisticsProficiency in data visualization, basic statistics, Excel, SQL
Work EnvironmentCollaborative projects, research-focused, often remote or nonprofit settingsData reporting, dashboard creation, data cleaning in nonprofit or community projects
Employer & Industry UsageTech nonprofits, research institutions, startupsCharities, educational organizations, community initiatives

Volunteer Data Scientist Machine Learning focuses on developing predictive models and advanced analytics, requiring programming and machine learning expertise. Volunteer Data Analyst emphasizes data interpretation, visualization, and reporting. Both roles support nonprofits but differ in technical complexity and focus areas.

What does a Volunteer Data Scientist in Machine Learning do?

A Volunteer Data Scientist in Machine Learning applies data analysis and machine learning techniques to help organizations solve problems, often for nonprofits or community projects. They may work on tasks such as cleaning and analyzing datasets, building predictive models, or creating data visualizations. Their work supports impactful decision-making and can help organizations operate more efficiently or achieve specific social goals. Volunteers often collaborate with teams to define project objectives and deliver actionable insights using their technical expertise.

How to get a job in data science machine learning with no previous experience?

To secure a volunteer data scientist machine learning role with no experience, focus on building foundational skills in programming (Python or R), data analysis, and machine learning algorithms through online courses and tutorials. Gain practical experience by working on personal projects, contributing to open-source datasets, or participating in competitions like Kaggle to demonstrate your abilities to potential employers or organizations. Certifications and a strong portfolio can also improve your chances of entry-level opportunities in this field.

Is ML a high paying job?

A volunteer data scientist specializing in machine learning typically does not receive a salary, as volunteering is unpaid. However, full-time machine learning roles are generally well-compensated, with salaries varying based on experience, location, and industry, often ranging from moderate to high six figures for experienced professionals. Skills in programming, statistical analysis, and familiarity with tools like Python or TensorFlow can influence earning potential.
What cities are hiring for Volunteer Data Scientist Machine Learning jobs? Cities with the most Volunteer Data Scientist Machine Learning job openings:
What are the most commonly searched types of Data Scientist Machine Learning jobs? The most popular types of Data Scientist Machine Learning jobs are:
What states have the most Volunteer Data Scientist Machine Learning jobs? States with the most job openings for Volunteer Data Scientist Machine Learning jobs include:
Volunteer Data Scientist Machine Learning jobs near you
AI / Machine Learning and Data Scientist

AI / Machine Learning and Data Scientist

Human Longevity, Inc.

South San Francisco, CA • On-site

Full-time

Posted 10 days ago

Job description

Job Summary:
Human Longevity, Inc. (HLI) is a global leader in precision health, combining cutting-edge genomics, imaging, AI-driven diagnostics, and elite medical expertise to redefine proactive healthcare. As an AI / Machine Learning and Data Scientist, you will build advanced data science, machine learning, and AI capabilities for data-driven healthcare applications, collaborating with cross-functional partners to unlock value from complex datasets.
Responsibilities:
• Support HLI’s mission by building advanced data science, machine learning, and AI capabilities for data-driven healthcare applications.
• Identify opportunities to leverage complex datasets for innovative, practical solutions across HLI’s healthcare and precision medicine environment.
• Collaborate with cross-functional experts to conceptualize, develop, and implement AI solutions tailored to a variety of healthcare use cases.
• Apply advanced machine learning methods, including Large Language Models (LLMs) and Natural Language Processing (NLP), to extract insights from large, unstructured medical datasets and inform decision-making.
• Build robust, data-driven solutions that translate complex analysis into practical applications addressing meaningful healthcare challenges.
• Design and develop scalable data pipelines that improve data quality, accessibility, and reliability across HLI’s core data infrastructure.
• Evaluate and implement AI agent platforms, including autonomous AI assistants and similar agentic AI frameworks, to automate complex workflows and enhance productivity.
• Create reusable and scalable tools that help unlock information across structured and unstructured data sources.
• Partner with technical and non-technical stakeholders to move models and workflows from concept to production-ready solutions.
Qualifications:
Required:
• Advanced degree in a quantitative discipline such as computer science, statistics, applied mathematics, biomedical informatics, biomedical engineering, or equivalent practical experience.
• 4+ years of experience applying advanced machine learning and AI techniques, including supervised and unsupervised methods, LLMs, and NLP, to clinical data.
• Direct experience working with Large Language Models and familiarity with prompt optimization approaches.
• Strong experience in machine learning, artificial intelligence, or predictive analytics in healthcare, life sciences, genomics, or related fields.
• Strong proficiency in Python, SQL, JavaScript/TypeScript, and/or R.
• Ability to work cross-functionally and drive projects in environments that may include ambiguity and evolving priorities.
Preferred:
• Experience with LLM workflows, including prompting, fine-tuning, and retrieval-augmented generation (RAG).
• Familiarity with software engineering principles and experience deploying algorithms in production environments.
• Experience partnering with clinical subject matter experts and cross-functional teams.
• Demonstrated ability to lead and execute technical projects from concept through implementation.
Company:
Human Longevity, Inc. Founded in 2013, the company is headquartered in San Diego, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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