Ai Experimental Systems Research Scientist (causal Learning & Adaptive Experimentation)

3M Company

Maplewood, MN, US
Base: $141,150 - $172,517; bonus/equity: variable ...
On-site
Adaptive experimental systems
Causal estimands and inference
Rigorous experimental control
3M Company is seeking an AI Experimental Systems Research Scientist specializing in causal learning and adaptive experimentation. The ideal candidate will possess a Ph.D. in a relevant field and a strong foundation in experimental design and statistical inference, contributing to the development of continuous learning systems

Job Summary

  • As an AI Experimental Systems Research Scientist, you will work on developing foundational methods for always-on learning systems that reason, experiment, and adapt in complex, non-stationary environments.
  • You will collaborate closely with researchers across statistics, cognitive science, and machine learning to design systems where experimentation, inference, and uncertainty are first-class components of the learning process.
  • This role is well suited for someone who enjoys working from first principles, designing rigorous experimental machinery, and translating statistical theory into systems that operate continuously in the real world.

Matching Summary

Match Score: 85

3M Company is seeking an AI Experimental Systems Research Scientist specializing in causal learning and adaptive experimentation. The ideal candidate will possess a Ph.D. in a relevant field and a strong foundation in experimental design and statistical inference, contributing to the development of continuous learning systems.

Salary

Base: $141,150 - $172,517; Bonus/Equity: variable incentive pay, if eligible; Benefits: Medical, Dental & Vision, Health Savings Accounts, Health Care & Dependent Care Flexible Spending Accounts, Disability Benefits, Life Insurance, Voluntary Benefits, Paid Absences and Retirement Benefits

Skills & Requirements

Must-have

  • adaptive experimental systems
  • causal estimands and inference
  • rigorous experimental control
  • always-on system behavior
  • research code implementation
  • epistemic correctness over performance

Nice-to-have

  • foundational methods for learning systems
  • reasoning, experimenting, and adapting
  • complex, non-stationary environments
  • identifiability, causal validity, epistemic calibration
  • first principles and statistical theory

Key Requirements

  • Ph.D. in Statistics, Biostatistics, Economics, Computer Science, Data Science, Operations Research, or related field
  • Deep grounding in experimental design and statistical inference
  • Implement research-grade statistical or experimental methods in a general-purpose programming language
  • Experience in research settings with evolving problem definitions

Work Rights

Not specified

Tailored Resume

Cover Letter