JMP 2027 Summer Internship; Causal Inference (Master's/Phd)
About The Position
JMP, a subsidiary of SAS, is hiring a summer intern for its Life Sciences division. The division develops advanced solutions across areas including causal inference, survival, genomics, clinical data science, and chemistry. It also works on emerging technologies and implementations involving large language models, agentic design, context engineering, user interface design, PyTorch, and XGBoost. The intern will help develop and evaluate causal inference methods and workflows for JMP products. The internship runs for 12 weeks, from May 18, 2027, through August 6, 2027. The dates are not flexible, and interns must be available to start in person at the Cary headquarters on May 18, 2027. The role offers a hybrid work approach aligned with team needs. Applicants must be legally authorized to work in the United States and must not require employment visa sponsorship now or in the future. Internship roles are not eligible for bonuses. Hourly rates for master’s and Ph.D. internship positions range from $29 to $49 per hour.
Requirements
- Be pursuing a master’s degree or preferably a Ph.D. in Statistics, Biostatistics, Computer Science, Data Science, Economics, Engineering, or another life-science-analytic-focused major.
- Not be graduating before December 2027.
- Have strong knowledge of causal inference.
- Have very strong written and verbal communication skills and coding skills.
- Demonstrate leadership abilities, initiative, and a willingness to go above and beyond.
- Be curious, passionate, authentic, and accountable, and interested in the future of analytics and embracing technology.
- Be legally authorized to work in the United States and not require employment visa sponsorship now or in the future.
- Be available to start in person at Cary headquarters on May 18, 2027, and work the internship dates through August 6, 2027.
Nice To Haves
- Knowledge of individual treatment effects.
- A Ph.D. is preferred.
Responsibilities
- Program in R, Python, C++, or another appropriate language to build new or state-of-the-art causal inference workflows and methods.
- Explore algorithms that could be adopted by JMP, including causal discovery, causal machine learning, LLM-based methods, and other cutting-edge approaches.
- Test, benchmark, document, and promote the work in written and/or video formats.
Benefits
- Hybrid work flexibility, with remote work aligned with team needs.
- Free SAS programming training and certification.
- Well-being programs, including an on-site Work/Life Center, Recreation and Fitness Center, Employee Assistance Program, and subsidized cafés.
- Hackathons, social events, and other opportunities to connect and engage.
- Opportunity to learn from company leaders and executives.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
