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Internship Causal Inference Jobs (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 ...

Instacart

OR · On-site

Overview We are looking for interns to join Instacart's Economics team. The ideal candidate for ... Expertise in causal inference with observational and experimental data. * Expertise in Python or R ...

Netflix

OR

$466K - $750K/yr

... causal inference, optimization, statistics, economics, and operations research. What you bring * Ph ... Actively mentors others, such as interns or junior peers. Generally, our compensation structure ...

Netflix

OR

$466K - $750K/yr

... causal inference, optimization, statistics, economics, and operations research. What you bring Ph.D ... Actively mentors others, such as interns or junior peers. Generally, our compensation structure ...

Netflix

Product Machine Learning Research Leader

... and causal inference excellence at Netflix. * Work closely with a wide range of partners ... interns. * Boost the visibility of Netflix research through research products such as external ...

Netflix

OR

... and causal inference excellence at Netflix. * Work closely with a wide range of partners ... interns. * Boost the visibility of Netflix research through research products such as external ...

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How much do internship causal inference jobs pay per hour?

As of May 31, 2026, the average hourly pay for internship causal inference in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

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 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 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 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.

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What cities are hiring for Internship Causal Inference jobs? Cities with the most Internship Causal Inference job openings:
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Internship Causal Inference jobs near you
Infographic showing various Internship Causal Inference job openings in the United States as of May 2026, with employment types broken down into 23% Internship, 8% Full Time, and 69% Part Time. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Biostatistics Internship (EDG-2026032)

Biostatistics Internship (EDG-2026032)

Edgewise Therapeutics

Boulder, CO • On-site

$20/hr

Full-time, Internship

Posted 25 days ago

Job description

Biostatistics Internship
About Edgewise Therapeutics:
At Edgewise, we are on a mission to discover new medicines that improve the lives of patients facing serious muscle disease. Our intimate knowledge of muscle biology and biophysics along with our ability to identify and design muscle specific precision small molecules have enabled us to rapidly advance our skeletal muscle and cardiac muscle product candidates into the clinic while also building a robust pre-clinical pipeline. With this focus on therapeutics designed to protect and improve muscle health, our goal is to dramatically enhance the lives of people living with progressive muscle disorders.
We have assembled an experienced and highly motivated leadership team with a strong track record in the biotechnology and pharmaceutical industry to build the leading, global muscle disease biopharmaceutical company. Come join us make a significant difference in the lives of patients!
Position Summary:
The Biostatistics intern will contribute to the development and application of innovative statistical methods for high-dimensional causal inference and machine learning to evaluate the effectiveness of therapeutics on health outcomes in serious skeletal and cardiac muscle diseases. This work will involve the analysis of high-dimensional biological data, with a focus on identifying treatment effects and improving understanding of disease mechanisms through advanced quantitative methods.
Key Responsibilities:
  • Clean, manage, and analyze complex, high-dimensional datasets using programming tools such as SAS, R and Python
  • Apply statistical, causal inference, and machine learning methods to real-world biomedical data
  • Develop reproducible workflows for data processing and analysis
  • Summarize findings through written reports and visualizations
  • Present analytical approaches and results to interdisciplinary team members
  • Review and summarize relevant scientific literature to inform ongoing research
  • Collaborate with team members on research design, methodology, and interpretation of results
  • Read, understand, and comply with all workplace health and safety policies; safe work practices; and company policies and procedures.
  • Perform other duties as assigned by supervisor.

Requirements:
Education, Experience, Skills:
  • Currently enrolled in a Doctorate program in Biostatistics, Statistics, Data Science, or a related quantitative field
  • Proficiency in programming languages such as SAS, R and/or Python
  • Strong foundation in statistical methods and data analysis
  • Experience or familiarity with causal inference methods
  • Experience or interest in machine learning methods, particularly for high-dimensional data
  • Ability to work with complex and large-scale datasets
  • Strong problem-solving and analytical skills
  • Effective written and verbal communication skills
  • Ability to work both independently and collaboratively in a team environment
  • Prior experience analyzing biomedical or high-dimensional datasets
  • Coursework or research experience in biostatistics, statistics, data science, or related field
  • Familiarity with causal inference frameworks and/or machine learning methods
  • Experience with data visualization and scientific reporting

Candidate must be located in Colorado.
Salary range: $20/hour; internship runs for 8-10 weeks
There is no deadline because the employer accepts applications on an ongoing basis.
Edgewise does not accept resumes from recruitment agencies for this position. Please do not send resumes to Edgewise employees or the company location. Edgewise is not responsible for any fees related to unsolicited resumes.

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