Startups · AI

Decision Research Scientist

Rwazi · Global (Remote) · Remote

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About Rwazi

Rwazi is the Decision AI company built on zero-party data from 5M+ contributors across 190+ countries. Sena is the decision intelligence platform that decides. Backed by Techstars.

About the role

Rwazi advances decision systems — software capable of structured reasoning under real-world constraints. The Decision Research Scientist applies formal reasoning, modeling, and experimentation to real enterprise decision problems.

What they're looking for

  • Strong grounding in decision theory, systems modeling, or applied reasoning
  • Experience formalizing ambiguous problems into structured frameworks
  • Comfort working with AI systems and reasoning architectures
  • Ability to design and evaluate experiments rigorously
  • Intellectual independence and systems thinking
  • Candidates may come from applied AI research, quantitative modeling, computational social science, economics, operations research, or advanced analytics domains
More about this role

Team: Research & Development

Reporting to: Head of R&D

Rwazi advances decision systems — software capable of structured reasoning under real-world constraints.

The Decision Research Scientist applies formal reasoning, modeling, and experimentation to real enterprise decision problems.

This role operates at the boundary between research and application.

It translates abstract decision theory, evaluation logic, and structured reasoning into practical system improvements that enhance Rwazi’s decision intelligence.

This is applied decision research — not academic isolation.

Designing formal decision frameworks for complex enterprise problems

Modeling tradeoffs, uncertainty, and signal ambiguity

Advancing structured reasoning methodologies

Testing and validating new decision architectures

Converting research insight into system-ready primitives

This role strengthens the reasoning depth of Rwazi’s decision engine.

Formalize complex business questions into structured decision systems

Model uncertainty, tradeoffs, and multi-variable constraints

Design evaluation logic for ambiguous signal environments

Develop structured judgment methodologies

Apply theoretical frameworks to real client...

Read the full posting on Rwazi's site ↗

R&D

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