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Contract Machine Learning Data Scientist Jobs in Berkeley, CA

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Data Scientist

San Francisco, CA

Data Scientist - San Francisco We are seeking a talented and experienced Data Scientist to join our ... Your expertise in data analysis, machine learning, and statistical modeling will enable you to ...

Info Way Solutions

Data Scientist

Fremont, CA · On-site

Infosys/Apple is seeking a highly skilled and motivated Data Scientist / Machine Learning Engineer to join their team. The role involves developing and implementing advanced analytics and machine ...

360 IT Professionals

Data Scientist

San Ramon, CA

Data Scientist Location: San Mateo, CA Contract: 6 Months Need 4 years + work experience with . Heavy deep learning AND Machine Learning AND Algorithm experience Additional Information All your ...

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Applies data science, machine learning and other analytical modeling methods to develop defensible and reproducible predictive models * Serves as the technical lead for the development of computer ...

Vizcom

Machine Learning Data Engineer

San Francisco, CA · On-site

$163 - $208/hr

... data. Your job will be to help turn that trail into a machine. A design session isn't a simple ... Dataset contracts and lineage: Implement systems that make examples traceable to their origin and ...

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All JobsContract Machine Learning Data Scientist JobsContract Machine Learning Data Scientist Jobs in Berkeley, CA

Contract Machine Learning Data Scientist information

See Berkeley, CA salary details

$45.9K

$150.3K

$240.6K

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

As of Sep 3, 2026, the average yearly pay for contract machine learning data scientist in Berkeley, CA is $150,286.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,600.00 and $166,500.00 per year, depending on experience, location, and employer.

What is a contract machine learning data scientist?

A Contract Machine Learning Data Scientist is a professional who works on a temporary or project-based basis to build, implement, and optimize machine learning models for organizations. Unlike full-time employees, contract data scientists are hired for specific projects or timeframes and may work independently or as part of a team. Their responsibilities typically include data cleaning, feature engineering, model selection, and communicating insights to stakeholders. Contract roles offer flexibility for both the professional and the employer, often focusing on specialized tasks or filling short-term skill gaps.

What are the key skills and qualifications needed to thrive as a contract machine learning data scientist?

To excel as a Contract Machine Learning Data Scientist, you need a strong background in statistics, programming (Python/R), and applied machine learning, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP, Azure), and version control systems is essential, along with experience deploying models in production. Exceptional problem-solving abilities, communication skills, and adaptability help you translate business needs into actionable data solutions and quickly integrate into new teams. These skills are crucial for delivering high-impact, reliable machine learning solutions on tight project timelines and in diverse organizational environments.

How do contract machine learning data scientists typically collaborate with in-house teams during a project?

Contract machine learning data scientists often work closely with in-house data teams, product managers, and engineers to align project goals and deliverables. They frequently participate in virtual meetings, code reviews, and regular progress updates to ensure transparency and seamless integration of their work. Effective communication and documentation are critical, as contractors may need to quickly adapt to the company's workflows and tools. This collaborative environment enables contractors to contribute specialized expertise while staying attuned to the broader objectives of the organization.

What is the difference between Contract Machine Learning Data Scientist vs Contract Data Scientist?

AspectContract Machine Learning Data ScientistContract Data Scientist
CredentialsTypically requires advanced degrees in data science, machine learning, or related fieldsRequires similar degrees but may have a broader focus on data analysis
Work EnvironmentOften in tech, finance, or healthcare industries focusing on ML projectsVaries across industries, including marketing, finance, and consulting
Employer UsageUsed by companies developing AI/ML solutions or productsEmployed for data analysis, reporting, and strategic insights
Search & Comparison IntentOften searched by those interested in AI/ML-specific rolesMore general, related to data analysis roles

The main difference is that Contract Machine Learning Data Scientists focus on developing and implementing machine learning models, while Contract Data Scientists may handle broader data analysis tasks without necessarily specializing in ML. Both roles require strong analytical skills and relevant credentials, but their project focus and industry applications differ.

What are popular job titles related to Contract Machine Learning Data Scientist jobs in Berkeley, CA?

For Contract Machine Learning Data Scientist jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Contract Machine Learning Data Scientist jobs in Berkeley, CA look for?

The top searched job categories for Contract Machine Learning Data Scientist jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Contract Machine Learning Data Scientist jobs?

Cities near Berkeley, CA with the most Contract Machine Learning Data Scientist job openings:

Contract Machine Learning Data Scientist jobs near you
Infographic showing various Contract Machine Learning Data Scientist job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $150,286 per year, or $72.3 per hour.

Machine Learning Data Scientist, Forecasting

OpenAI

San Francisco, CA • On-site

$230K - $385K/yr

Full-time

Posted 21 days ago

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.

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