Causal Inference Summer Research Internship (Hybrid)

SAS; Idaho; Hybrid; USD 40,000 - 68,000; Full time

Benefits offered by this job

Hybrid work flexibility

Free SAS programming training

Face time with leaders

Job summary

JMP, a subsidiary of SAS, invites a highly skilled intern to join the Life Sciences team. You will contribute to causal inference workflows, coding in R/Python/C++, and exploring modern analytics methods in a collaborative environment.

The program emphasizes development, culture, and community, with hybrid work options and opportunities to learn from company leaders and executives. Applicants must pursue a Master’s or PhD and demonstrate leadership and strong communication.

Qualifications

• Pursuing a Master’s or PhD in Statistics, Biostatistics, CS, Data Science, Economics, Engineering, or life-science analytics-focused major, not graduating before December 2027.
• Strong knowledge about causal inference; individual treatment effect is a plus.
• Very strong communication and coding skills; both written and verbal.
• Leadership abilities and initiative shown in past experiences.

Responsibilities

• Program in R/Python/C++ to build causal inference workflows/methods.
• Explore algorithms like causal discovery, causal ML, LLM-based methods for JMP apps.
• Test, benchmark, document, and promote this work (written or video).

Skills

R

Python

C++

Causal inference

Communication

Education

Master’s or PhD in Statistics/CS/Data Science/Engineering

Tools

R

Python

C++

Job description

JMP, a subsidiary of SAS, invites a highly skilled intern to join the Life Sciences team. You will contribute to causal inference workflows, coding in R/Python/C++, and exploring modern analytics methods in a collaborative environment.

The program emphasizes development, culture, and community, with hybrid work options and opportunities to learn from company leaders and executives. Applicants must pursue a Master’s or PhD and demonstrate leadership and strong communication.