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Volunteer Data Scientist Machine Learning Jobs in California

DATA SCIENTIST II

Norco, CA · On-site

$115 - $130/hr

In this role, you will apply advanced data analytics and machine learning techniques to explore ... voluntary benefits. Our goal is to grow together and enjoy the work that we do as a team. VSolvit ...

... Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep ... scientists, and ML Infrastructure engineers to deliver amazing user experiences! Description ...

DATA SCIENTIST II

Norco, CA · On-site

$115K - $130K/yr

In this role, you will apply advanced data analytics and machine learning techniques to explore ... voluntary benefits. Our goal is to grow together and enjoy the work that we do as a team. VSolvit ...

Principal Data Scientist

Oakland, CA · On-site

$128 - $148/hr

Master's Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field. * Experience in Data Science ...

What you'll bring * 4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a ... related quantitative role. * Experience in logistics, marketplaces, supply chain, operations ...

What you'll bring * 4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a ... related quantitative role. * Experience in logistics, marketplaces, supply chain, operations ...

Working at the intersection of machine learning, data science, and product quality, you will influence critical decisions through data-driven insights and technical leadership. You will collaborate ...

Showing results 21-40

Volunteer Data Scientist Machine Learning information

What skills and qualifications are needed to thrive as a volunteer data scientist machine learning?

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.

How does a volunteer data scientist machine learning 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 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.

What are the most commonly searched types of Data Scientist Machine Learning jobs in California?

The most popular types of Data Scientist Machine Learning jobs in California are:

What cities in California are hiring for Volunteer Data Scientist Machine Learning jobs?

Cities in California with the most Volunteer Data Scientist Machine Learning job openings:

Machine Learning Data Scientist, Forecasting

OpenAI

San Francisco, CA • On-site

$230K - $385K/yr

Full-time

Posted 2 days ago

New


Job description

About the Team
The Strategic Finance team at OpenAI plays a critical role in shaping the company's long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we're building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.
We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI's full potential.
About the Role
We're looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You'll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability.
This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You'll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
  • Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains.
  • Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
  • Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability.
  • Contribute to self-service forecasting tools and internal platforms, enabling teams across OpenAI to access and act on real-time predictions.
  • Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches.
  • Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks.
  • Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making.

You might thrive in this role if you have:
  • Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
  • 7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.
  • Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability.
  • Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
  • Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
  • Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
  • Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0→1.

Bonus if you have:
  • Experience building or scaling forecasting platforms in a high-growth company.
  • Familiarity with causal inference, Bayesian forecasting
  • Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments.

#LI-NM2
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.