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Agent Based Modeling Scientist Jobs in San Rafael, CA

(Senior) ML Scientist

South San Francisco, CA · On-site

$183K - $238K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... graph-based modeling, causal structure learning, single cell omics, or imaging modalities. Your ... You will be part of a cross-functional team of life scientists, data scientists, bioengineers ...

... agent-based applications. Responsibilities : • Co-architect and co-build production AI agents ... model agents. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of ...

... modeling, scientific discovery). Start Date * Urgent ; applications reviewed on a rolling basis. Application Process (Takes 20-30 mins to complete) * Upload resume * AI interview based on your resume

Posted today

Senior Data Scientist

Brisbane, CA

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... based on measured impact on agent quality. Develop analytical features, embeddings, classifiers ... Assess model and agent outputs for quality, uncertainty, calibration, bias, hallucination risk ...

Showing results 21-40

Agent Based Modeling Scientist information

See San Rafael, CA salary details

$36.8K

$56.4K

$107.6K

How much do agent based modeling scientist jobs pay per year?

As of Aug 19, 2026, the average yearly pay for agent based modeling scientist in San Rafael, CA is $56,373.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,600.00 and $54,600.00 per year, depending on experience, location, and employer.

What is an agent based modeling scientist?

An Agent Based Modeling (ABM) Scientist is a researcher or professional who develops computational models that simulate the actions and interactions of autonomous agents (such as individuals, groups, or entities) to study complex systems. These scientists use ABM techniques to analyze how the behavior of individual agents leads to collective outcomes, often in fields like biology, economics, social sciences, and epidemiology. Their work involves designing models, running simulations, and interpreting data to gain insights into system dynamics and emergent phenomena.

How does an agent based modeling scientist typically collaborate with interdisciplinary teams during a project?

Agent Based Modeling Scientists often work closely with experts from fields such as economics, epidemiology, engineering, and computer science to ensure that models accurately reflect real-world systems. Collaboration usually involves regular meetings to define system parameters, validate model assumptions, and interpret simulation results. Effective communication is essential, as team members may not always be familiar with agent-based modeling concepts. Sharing insights and translating technical findings for broader audiences helps ensure models are both robust and actionable for decision-makers.

What are the key skills and qualifications needed to thrive as an agent based modeling scientist, and why are they important?

To thrive as an Agent Based Modeling Scientist, you need expertise in computational modeling, systems theory, and a strong background in mathematics or related fields, often supported by an advanced degree. Proficiency with programming languages such as Python, Java, or NetLogo and familiarity with simulation software are typically required. Analytical thinking, problem-solving, and the ability to communicate complex concepts clearly are valuable soft skills in this role. These skills are crucial for accurately developing, interpreting, and conveying insights from agent-based models to inform research or decision-making.

What is the difference between Agent Based Modeling Scientist vs Data Scientist?

AspectAgent Based Modeling ScientistData Scientist
Required CredentialsMaster's or PhD in computer science, mathematics, or related fields; experience with modeling and simulationDegree in statistics, computer science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentResearch labs, academia, or industry focused on simulation and modeling projectsBusiness, tech companies, or consulting firms analyzing large datasets
Industry UsageResearch, simulation, complex systems modelingData analysis, predictive modeling, business insights

While both roles require strong analytical skills and programming knowledge, an Agent Based Modeling Scientist specializes in creating simulations of autonomous agents within complex systems, whereas a Data Scientist focuses on analyzing and interpreting large datasets to inform business decisions.

What cities near San Rafael, CA are hiring for Agent Based Modeling Scientist jobs?

Cities near San Rafael, CA with the most Agent Based Modeling Scientist job openings:

Research Economist, Economic Research

Anthropic

San Francisco, CA

Full-time

Re-posted 29 days ago


Job description

About the Role

As an Economist at Anthropic, you will work to measure and understand AI's effects on the global economy. You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic's internal business and product decisions.

Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (Clio), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks.

Responsibilities
  • Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including quarterly reports and industry-specific deep dives
  • Design and conduct empirical research on AI's economic effects, drawing on external data sources and the privacy-preserving measurement systems internally
  • Develop new methodological approaches for studying AI's impact on:
    • Labor markets and the future of work
    • Productivity and task transformation
    • Economic inequality and displacement
    • Industry-specific disruption and adaptation
    • Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios
  • Develop causal-inference tooling - e.g. surrogate indexes, heterogeneous-effect pipelines - to help Anthropic evaluate the downstream economic consequences of its own compute, product, and pricing decisions
  • Build and maintain relationships with academic institutions, policy think tanks, and other research partners
  • Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection
  • Translate research insights into actionable recommendations for both product decisions and policy discussions
  • Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders
You May Be a Good Fit If You Have
  • PhD in Economics
  • Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning
  • Experience relevant to the study of AI's impact on the economy, including:
    • Labor market analysis and occupational change
    • Task-based approaches to technological transformation
    • Large-scale data analysis and econometric methods
    • Large language models for social science research
    • Policy-relevant economic research
    • Experimental and quasi-experimental methods for causal inference
    • Macroeconomic modeling and time series forecasting
    • Agent-based modeling or large-scale simulation
  • Technical skills including:
    • Proficiency in Python, R, SQL, or similar tools for large-scale data analysis
    • Experience working with novel datasets and measurement systems
    • Comfort learning new technical tools and frameworks
  • Demonstrated ability to:
    • Lead complex research projects from conception to publication
    • Communicate technical findings to diverse audiences
    • Build relationships across academic, policy, and industry communities
  • Strong interest in ensuring AI development benefits humanity
  • Comfort working with AI systems and ability to think critically about their capabilities and limitations
Some Examples of Our Recent Work
  • Anthropic Economic Index Report: Economic Primitives
  • Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption
  • Estimating AI productivity gains from Claude conversations
  • The Anthropic Economic Index
Additional Information

For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact.

Application Question

Please provide a writing sample, preferably a job-market paper or other article that showcases your research and technical expertise.

Deadline to apply: None. Applications are reviewed on a rolling basis