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Internship Causal Inference Jobs in Baltimore, MD

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Internship Causal Inference information

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$9

$17

$23

How much do internship causal inference jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for internship causal inference in Baltimore, MD is $17.20, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $19.09 per hour, depending on experience, location, and employer.

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 Baltimore, MD? The most popular types of Causal Inference jobs in Baltimore, MD are:
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What cities near Baltimore, MD are hiring for Internship Causal Inference jobs? Cities near Baltimore, MD with the most Internship Causal Inference job openings:
Internship Causal Inference jobs near you
Post Doctoral Fellow - Biostatistics and Data Science

Post Doctoral Fellow - Biostatistics and Data Science

University of Maryland, Baltimore

Baltimore, MD • On-site

$48K - $66K/yr

Full-time

PTO

Posted 25 days ago

University Of Maryland, Baltimore rating

7.7

Company rating: 7.7 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

228th of 555 rated colleges and universities

Job description

Job Description
POSTDOCTORAL FELLOW: The Maryland Psychiatric Research Center (MPRC) at the University of Maryland School of Medicine is recruiting a Postdoctoral Fellow for the Biostatistics and Data Science Laboratory led by Dr. Shuo Chen.
The is an internationally renowned research center, which is dedicated to providing treatment to patients with schizophrenia and related disorders, educating professionals and consumers about schizophrenia, and conducting basic and translational research into the manifestations, causes, and treatment of schizophrenia.
EssentialFunctions:
• Developing new statistical methods to model multimodal neuroimaging data, multi-omics data, electronic health record (EHR) and genetics data which are measured by longitudinally and cross-sectionally.
• Developing and applying machine learning and AI approaches to identify interactive topological relationships between various imaging modalities and multi-omics during aging and development.
• Implementing computationally intensive algorithms on high-performance computational clusters.
• Developing AI/ML-based causal inference models for real-world evidence applications (e.g., target trial emulations- TTE)
• Developing data integration methods to combine multiple massive datasets (UKBB, HCP, ENIGMA, and etc) and local trials and observational studies (e.g, UMMS EHR).
• Manuscript drafting and preparation.
• Performing other duties as assigned.
Qualifications
Qualifications
Minimum Qualifications:
Education:A Ph.D. degree in a quantitative field such as statistics, biostatistics, bioinformatics, computational biology, human genetics, computer science, or a closely related area is required.
Experience:Demonstrated experience in strong optimization computational skills, proficiency in one of the programming languages R, Matlab, and Python, and expertise in high-performance clusters are required.
Knowledge, Skills, and Abilities:
• Knowledge in advanced statistical theory and methods.
• Strong optimization and computational skills to process large-scale medical images and analyze multi-modal data effectively.
• Excellent interpersonal skills, including a positive and professional orientation towards faculty, staff, university officials, partner organizations, and other stakeholders.
The stipend for Postdoctoral Fellows is competitive and aligned with the number of full years of relevant postdoctoral experience. Relevant experience may include research, teaching, clinical duties, internships, or other work in a health-related field beyond the qualifying doctoral degree. Stipend levels are determined to meet or exceed the current listed on the website. Postdoctoral Fellows at the University of Maryland also receive a comprehensive benefits package that includes 10 days of annual leave, 15 days of sick leave, 3 personal days, all university-recognized holidays, and may also qualify for additional leave options.
For immediate consideration, please send a cover letter and a recent CV, including names and contact information of three references, to this link
To apply for this position or to seek additional information, please contact Dr. Chen at
For additional questions after application, please email at
UMB is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy.

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