Own the technical architecture and end-to-end delivery of each workstream, from data foundations through models and optimisation to evidence proving effectiveness

- Serve as the technical face of the engagement
- Run methodology reviews, steering sessions, and executive readouts for client leaders and partners
- Lead a pod of machine‐learning and data engineers
- Set standards for code review, testing, reproducibility, and documentation
- Build and operate production data pipelines on Google Cloud Platform and Big Query at large scale across billions of rows
- Apply cost discipline and data‐governance controls
- Design, ship, and validate propensity, uplift, visitation‐frequency, and offer‐adoption models
- Apply causal inference in production, including uplift modelling, matched‐control difference‐in‐differences, double machine learning, holdout and experiment design, and power analysis
- Build optimisation engines using mixed‐integer and linear programming, assignment methods, and scheduling methods
- Maintain architecture documents, decision registers, and evidence packs suitable for adversarial technical review
- Translate technical work into plain language for business and executive audiences
- Collaborate with client business and technical teams and advisory and consulting partners

Requirements

- Ten or more years building and shipping production data and machine‐learning systems, including time spent leading technically or leading a team
- Deep, hands‐on Python and SQL
- Production data engineering on a major cloud platform
- Applied causal inference and experimentation, including uplift modelling, difference‐in‐differences, double machine learning, and power analysis
- Mathematical optimisation applied to operational problems, including mixed‐integer or linear programming and assignment or scheduling problems
- Track record of client‐facing delivery and presenting to senior executives and external delivery partners




- Experience building agentic workflows and integrating LLMs and agentic systems into production solutions
- Production‐grade testing, reproducibility, data lineage, and documentation
- Comfort operating in regulated, high‐governance data environments
- Right to work in Australia, or a base in a time zone within about two hours of Australian Eastern Time
- Resume and application materials must be submitted in English
- Melbourne preferred; strong candidates elsewhere in Australia considered
- Experience with Google Cloud Platform and Big Query ideal; AWS, Databricks, or Microsoft Azure experience transfers well
- Domain experience in gaming, casino, hospitality, or loyalty and marketing analytics is a nice‐to‐have
- Experience with recommendation systems, marketing and offer optimisation, or workforce and roster optimisation is a nice‐to‐have
- Experience integrating vendor systems for yield management, workforce management, or player and table tracking is a nice‐to‐have
- Background in responsible‐gaming, anti‐money‐laundering, or privacy‐by‐design is a nice‐to‐have
- Consulting or client‐embedded delivery experience is a nice‐to‐have

Core Competencies

Demonstrates expertise in building and delivering production data and machine‐learning systems, with a robust focus on applied causal inference, mathematical optimization, and client‐facing delivery. Proficient in managing technical architecture and collaborating with cross‐functional teams in regulated data environments.

Highest‐signal resume keywords

- Python
- SQL
- Google Cloud Platform
- Big Query
- Causal Inference

Hard Skills

- Machine Learning
- Data Engineering
- Mathematical Optimization
- Production Data Pipelines
- Uplift Modelling
- Mixed‐Integer Programming
- Linear Programming
- Testing and Reproducibility
- Data Governance
- Documentation

Soft Skills

- Client‐Facing Delivery
- Communication
- Leadership

Industry Keywords

- Gaming
- Casino
- Hospitality
- Loyalty Analytics
- Marketing Analytics

Tools & Technologies

- AWS
- Databricks
- Microsoft Azure

📌 Principal AI Engineer – Technical Lead (Melbourne)
🏢 Jobtailor
📍 Melbourne