ZipRecruiter

Log In

1

Internship Causal Inference Jobs in California (NOW HIRING)

Stripe

PhD Data Scientist, Intern

San Francisco, CA · On-site

Through the internship, you will work with many systems and technologies, gain experience in ... Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure ...

Faire

Data Science Intern

San Francisco, CA · On-site

$75/hr

Data Science Internship - Multiple Teams Faire leverages machine learning and data insights to ... Knowledge of statistical techniques including experimentation and causal inference * Experience ...

next page

Showing results 1-20

All JobsInternship Causal Inference JobsInternship Causal Inference Jobs in California

Internship Causal Inference information

What types of projects and team collaborations can I expect during an Internship in Causal Inference?

As an intern in Causal Inference, you will typically work on projects focused on analyzing data to determine cause-and-effect relationships, such as assessing the impact of interventions or policy changes. You may collaborate with data scientists, statisticians, and domain experts, contributing to experimental design, data cleaning, and the application of statistical methods. Interns often participate in weekly team meetings, present findings, and receive mentorship from senior researchers. This hands-on experience provides valuable exposure to both technical skills and interdisciplinary teamwork, which are crucial for growth in quantitative research roles.

What are the key skills and qualifications needed to thrive as an Internship Causal Inference, and why are they important?

To thrive in an Internship Causal Inference role, you need a solid background in statistics, econometrics, and data analysis, typically supported by coursework or degrees in statistics, economics, or related quantitative fields. Familiarity with statistical programming languages such as R or Python, and experience with causal inference frameworks and tools like propensity score matching or regression discontinuity, are commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret results and collaborate with research teams. These skills and qualities are essential to ensure rigorous and meaningful analysis that informs data-driven decisions.

What is the difference between Internship Causal Inference vs Data Analyst?

AspectInternship Causal InferenceData Analyst
Required CredentialsUndergraduate or graduate in statistics, economics, or related fieldsDegree in statistics, data science, or related fields
Work EnvironmentResearch-focused, often in academia or research institutionsBusiness, corporate, or consulting settings
Employer & Industry UsageUniversities, research labs, tech companiesFinance, marketing, healthcare, tech companies
Comparison Search IntentUnderstanding causal inference techniques during internshipsAnalyzing data to inform business decisions

Internship Causal Inference roles focus on applying statistical methods to identify cause-effect relationships, often in research settings. Data Analyst roles involve interpreting data to support business strategies. While both require analytical skills, causal inference internships emphasize research and advanced statistical techniques, whereas data analyst positions focus on data processing and reporting.

What is an Internship in Causal Inference?

An Internship in Causal Inference is a temporary position, typically for students or early-career professionals, that focuses on learning and applying methods to determine cause-and-effect relationships in data. Interns in this field work with statistical models, experimental designs, and software tools to analyze data and infer causal relationships, often in fields like economics, public health, or data science. These internships provide hands-on experience with real-world datasets, mentorship from experienced researchers, and opportunities to contribute to ongoing projects. Participants gain valuable skills in programming, statistical analysis, and research methodology, which are highly sought after in both academia and industry.
What are the most commonly searched types of Causal Inference jobs in California? The most popular types of Causal Inference jobs in California are:
What are popular job titles related to Internship Causal Inference jobs in California? For Internship Causal Inference jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Causal Inference jobs in California look for? The top searched job categories for Internship Causal Inference jobs in California are:
What cities in California are hiring for Internship Causal Inference jobs? Cities in California with the most Internship Causal Inference job openings:
Internship Causal Inference jobs near you
Infographic showing various Internship Causal Inference job openings in California as of June 2026, with employment types broken down into 23% Internship, and 77% Full Time. Highlights an 92% In-person, and 8% Remote job distribution.
PhD Data Scientist, Intern

PhD Data Scientist, Intern

Stripe

San Francisco, CA • On-site

Internship

Posted 15 days ago

Job description

Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies-from the world's largest enterprises to the most ambitious startups-use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
About the team
Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.
What you'll do
About the internship experience
Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products.
Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.
We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.
Responsibilities
You will:
  • Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
  • Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
  • Influence business actions and strategy by developing actionable insights through metrics and dashboards
  • Drive the collection of new data and the refinement of existing data sources
  • Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
  • Present your work to the Data Science team, partner teams, and fellow interns
Who you are
Minimum requirements
We're looking for someone who has:
  • Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
  • Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
  • Knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
  • Experience communicating and collaborating with multidisciplinary stakeholders in a team environment
Preferred qualifications
You also likely have:
  • Experience writing and debugging data pipelines
  • Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
  • Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

Apply