Chief Algorithmic Defense Scientist

Lewis & Grey International; Sydney; Hybrid; AUD 180,000 - 320,000; Full time

Benefits offered by this job

Equity participation

Competitive compensation package

Job summary

Lewis & Grey International seeks a Lead Data Scientist for Algorithmic Defense to reverse engineer black box algorithms and build defensive infrastructure protecting clients from bias and synthetic fraud. You will lead the development of our proprietary Forensic Content Audit tools and Knowledge Graph strategies to drive defensible, data-driven outcomes.

You will work across NLP, ML theory, and graph databases to quantify reputational alpha and defend clients in complex regulatory environments.

Qualifications

• PhD or Masters in CS/Statistics/Mathematics/Computational Linguistics.
• Strong ML theory and NLP background beneficial.
• Experience with adversarial thinking and reputation systems preferred.

Responsibilities

• Adversarial Algorithm Analysis: study ranking factors and moderation policies; model calcification velocity of negative content.
• Develop and deploy Knowledge Graph Injection strategies to counter AI hallucinations.
• Synthetic Identity & Bot Detection: build classifiers to distinguish real vs synthetic reviews.
• Quantifying Reputational Alpha: correlate sentiment with financial metrics for ROI analysis.
• Lead the development of the Forensic Content Audit tools and the Lewis & Grey Intelligence Platform.

Skills

Adversarial thinking

Mathematical ML

Economic insight

Linguistic precision

Python

R

SQL

Education

PhD in CS/Statistics/Math/Computational Linguistics

Tools

Python

R

SQL

Hugging Face

spaCy

Pinecone

Milvus

Neo4j

Job description

Lewis & Grey International seeks a Lead Data Scientist for Algorithmic Defense to reverse engineer black box algorithms and build defensive infrastructure protecting clients from bias and synthetic fraud. You will lead the development of our proprietary Forensic Content Audit tools and Knowledge Graph strategies to drive defensible, data-driven outcomes.

You will work across NLP, ML theory, and graph databases to quantify reputational alpha and defend clients in complex regulatory environments.