Rwazi Logo

Rwazi

Decision Intelligence Analyst

Reposted 8 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Canada
Mid level
In-Office or Remote
Hiring Remotely in Canada
Mid level
Own decision quality by evaluating AI-generated decisions, identifying reasoning failures, designing feedback and training loops, defining decision-quality metrics, and collaborating with Product, R&D, and Engineering to improve robustness, explainability, and drift detection.
The summary above was generated by AI
Decision Intelligence Analyst

Team: Product
Location: Flexible / Remote
Reporting to: VP of Product

Role Overview

Rwazi’s platform produces decision-grade outputs powered by structured reasoning and AI-assisted judgment.

The Decision Intelligence Analyst owns decision quality.

This role evaluates system outputs, identifies reasoning weaknesses, and strengthens AI judgment through structured feedback and training loops.

It ensures the platform does not merely generate outputs — but generates sound, defensible decisions.

The Decision Intelligence Analyst is the quality control layer for decision intelligence.

Core Mandate

The Decision Intelligence Analyst is accountable for:

  • Evaluating decision outputs for logical integrity and sound reasoning

  • Identifying patterns of judgment failure or inconsistency

  • Designing structured feedback loops to improve AI reasoning

  • Training and refining AI judgment frameworks

  • Defining measurable standards for decision quality

This role governs the reliability of Rwazi’s decision engine.

Key ResponsibilitiesDecision Output Evaluation
  • Review system outputs for logical coherence and reasoning rigor

  • Assess signal interpretation accuracy

  • Identify tradeoff miscalculations or flawed inference pathways

  • Document recurring reasoning gaps

AI Judgment Training
  • Create structured examples to refine reasoning performance

  • Develop edge-case libraries for training robustness

  • Formalize evaluation rubrics for decision quality

  • Collaborate with R&D to improve reasoning architecture

Quality Standards & Metrics
  • Define measurable criteria for decision-grade output

  • Track improvements in reasoning consistency

  • Monitor drift in output quality over time

  • Establish acceptance thresholds for release

Failure Mode Analysis
  • Identify systemic reasoning weaknesses

  • Surface blind spots in signal modeling

  • Propose structured adjustments to logic layers

  • Escalate structural flaws early

Cross-Functional Collaboration
  • Partner with Product to align quality with roadmap goals

  • Collaborate with R&D on advanced reasoning improvements

  • Provide structured feedback to Engineering when system behavior deviates

Role Impact

Strong performance in this role results in:

  • Higher confidence in decision outputs

  • Reduced reasoning inconsistencies

  • Improved explainability

  • Faster detection of system drift

  • Stronger enterprise trust

This role protects the intellectual credibility of the platform.

What This Role Is Not
  • This is not general QA

  • This is not surface-level data validation

  • This is not simple output review

This role evaluates reasoning quality, not formatting correctness.

Qualifications and Profile

We are looking for individuals who demonstrate:

  • Strong analytical and logical reasoning ability

  • Experience evaluating AI systems, decision frameworks, or complex models

  • Comfort dissecting multi-step reasoning chains

  • Ability to formalize judgment criteria

  • Strong written clarity and structured thinking

  • Comfort working with ambiguity and edge cases

Candidates may come from applied AI evaluation, consulting, operations research, economics, philosophy of logic, or technically rigorous analytical fields.

Cultural Fit

We value analysts who:

  • Obsess over reasoning integrity

  • Question outputs rather than accept them

  • Care about intellectual rigor

  • Prefer structured evaluation over intuition

  • Are comfortable holding high standards

How Candidates Are Evaluated

Candidates are evaluated based on:

  • Their ability to critique and improve structured reasoning

  • Clarity of their evaluation frameworks

  • Depth of logical analysis

  • Ability to identify hidden failure modes

  • Their rigor in defining measurable quality standards

We prioritize demonstrated reasoning discipline over titles alone.

Summary

The Decision Intelligence Analyst safeguards the quality and integrity of Rwazi’s decision engine.

This role ensures that as AI capabilities expand, decision outputs remain structured, defensible, and enterprise-grade.

Similar Jobs

An Hour Ago
Remote or Hybrid
Toronto, ON, CAN
Senior level
Senior level
eCommerce • Fashion • Retail • Sales • Wearables • Design
Lead regional retail training and customer experience initiatives, deliver and implement sales, service, and clienteling programs, monitor KPIs, coach store teams and managers, support onboarding and digital tool adoption (Coach Journey, Client Compass), and drive consistent brand service standards across the market.
Top Skills: Client CompassCoach JourneyExcelMS OfficePowerPointWord
3 Hours Ago
In-Office or Remote
CA
Mid level
Mid level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Build and operate ingestion, reconciliation, and reporting systems that reconcile card-network and partner settlement files against internal transactions. Deliver end-to-end features for traceability, accounting journals, tax and regulatory reporting, and compliance tooling while ensuring reliability, scalability, and data privacy.
Top Skills: Ai ToolsAirflowAWSBigQueryCi/CdDelta LakeGoHadoopIso-8583JavaKafkaKubernetesObservabilityPysparkPythonSnowflakeSparkSQLTemporalTerraform
3 Hours Ago
In-Office or Remote
CA
Senior level
Senior level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.
Top Skills: Ai/MlAlgorithmic Impact AssessmentGenerative AiLlmsModel CardsModel Monitoring

What you need to know about the Toronto Tech Scene

Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account