Decision Intelligence Analyst

Role overview

This opportunity is posted on behalf of a partner employer that will handle all applications and subsequent hiring steps. The partner is seeking a Decision Intelligence Analyst in Australia.

The role is centered on an AI-based decision intelligence platform where the goal is not merely to produce outputs, but to make sure those outputs are logically robust, defensible, and suitable for real decisions. In this position, you will serve as a quality checkpoint for reasoning systems, assessing how conclusions are reached rather than only reviewing the final result. You will partner with product and research teams to improve the reliability of AI judgment frameworks. The work is analytical, research-oriented, and strongly rooted in structured thinking and ongoing refinement. Your contribution will directly affect how trustworthy and accurate advanced decision systems become.

Accountabilities

• Review AI-generated decision outputs to check for logical coherence, strength of reasoning, and overall soundness, while spotting weaknesses in multi-step inference and trade-off analysis.
• Identify recurring signs of reasoning breakdowns, inconsistency, or drift, and record repeated issues across decision paths.
• Create structured review methods and evaluation rubrics that help improve the quality of AI judgment over time.
• Help build training frameworks, including collections of edge cases and structured examples used to refine models.
• Set and uphold measurable benchmarks for decision-quality outputs so results stay consistent and dependable.
• Work alongside product, research, and engineering stakeholders to align reasoning-quality improvements with system growth and roadmap goals.
• Call out deeper logic issues early and recommend structured changes that strengthen the decision architecture.

Requirements

• Strong analytical ability with the skill to break complex, multi-step reasoning into parts and assess it critically.
• Hands-on exposure to AI systems, decision frameworks, applied analytics, or other structured problem-solving settings.
• Capability to turn subjective judgment into clear evaluation criteria and measurable standards.
• Excellent written communication, supported by precise and well-organized thinking.
• Comfort dealing with ambiguity, edge cases, and incomplete information while keeping analysis disciplined.
• Experience or background may come from applied AI evaluation, consulting, economics, operations research, philosophy of logic, or similar rigorous analytical disciplines.
• A mindset that challenges assumptions, refines reasoning, and improves systems instead of accepting outputs at face value.

Benefits

• Chance to contribute to advanced AI-driven decision intelligence systems with meaningful business impact.
• Remote or flexible work arrangements may be available depending on the organization’s setup.
• Exposure to advanced AI research and cross-functional work with product and engineering teams.
• Competitive pay aligned with experience and skill level.
• Direct influence on the reliability and quality of enterprise-grade AI decision systems.
• A fast-moving, intellectually demanding environment focused on learning and continuous improvement.

How the application process works

The application is reviewed through an AI-assisted matching process designed to assess fit quickly, consistently, and fairly against the role’s core requirements. The strongest matches are shortlisted and shared with the hiring company, while interviews and assessment steps are managed internally by their team.

Privacy and data processing notice

By applying, you acknowledge that the recruitment partner may process your personal data to assess your candidacy and share relevant details with the employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. You may exercise your rights, including access, rectification, erasure, and objection, at any time.

The recruitment process may also use AI tools to support parts of application review, résumé analysis, response evaluation, and detection of possible inconsistencies or verification signals using the information provided. These tools assist recruiters but do not replace human judgment, and final hiring decisions are made by people. For more information about data processing, you may contact the recruiter.