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Internship Causal Inference Jobs (NOW HIRING)

Docugami

Data Science PhD Intern

Kirkland, WA

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work ... causal inference, and other related disciplines * Programming skills and familiarity of modern ML ...

Docugami

Data Science PhD Intern

Kirkland, WA · On-site

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work ... causal inference, and other related disciplines * Programming skills and familiarity of modern ML ...

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Internship Causal Inference information

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How much do internship causal inference jobs pay per hour?

As of Jun 21, 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 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.
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What cities are hiring for Internship Causal Inference jobs? Cities with the most Internship Causal Inference job openings:
What are the most commonly searched types of Causal Inference jobs? The most popular types of Causal Inference jobs are:
What states have the most Internship Causal Inference jobs? States with the most job openings for Internship Causal Inference jobs include:
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Internship Causal Inference jobs near you
Infographic showing various Internship Causal Inference job openings in the United States as of June 2026, with employment types broken down into 39% Internship, 14% As Needed, 24% Full Time, and 23% Part Time. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)

Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)

Unity Technologies

Mountain View, CA

Other

Medical, Life, Retirement, PTO

Posted 5 days ago

Job description

The opportunity
Unity's Vector AI team builds the machine learning systems that decide which ads reach which players - across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale.

We are building the next generation of these systems. The frontier has shifted - large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter.

What you'll be doing

  • Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
  • Develop user understanding systems - conversion prediction, behavioral modeling, and value estimation - that operate across billions of impressions.
  • Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
  • Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
  • Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
  • Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.

What we're looking for

  • PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
  • Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
  • Experience working with large-scale data and ML systems, whether through research or industry internships.
  • Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • A track record of rigorous, high-quality research - publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
  • Strong written and verbal communication skills - able to make complex ideas accessible across technical and non-technical audiences.

You might also have

  • Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
  • Hands-on experience with production ML pipelines - training at scale, feature engineering, or experimentation infrastructure.
  • Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
  • Familiarity with agentic AI approaches - multi-step reasoning, tool use, or human-AI collaboration frameworks.
  • Exposure to causal inference, uplift modeling, or A/B testing at scale.
  • Genuine curiosity about applied research and the drive to see ideas through to impact.

Additional information

  • Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

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