Lead Analytics Engineer at Crown Resorts
Southbank VIC 3006, , Australia -
Full Time


Start Date

Immediate

Expiry Date

06 Oct, 25

Salary

0.0

Posted On

06 Jul, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Computer Science, Data Engineering, Statistics, Analytics, Hospitality Industry, Data Science

Industry

Information Technology/IT

Description

JOB DESCRIPTION

You’ll be responsible for driving data initiatives across Gaming, F&B, Hotels, Conferences, and Customer departments - across our three locations; Melbourne, Sydney and Perth.
You’ll use the Google Cloud Platform to develop and execute data strategies, oversee data acquisition and structuring, and operationalise advanced data models to support real-time decision-making. This role requires strong leadership, technical expertise in SQL, Python, R, and data visualization tools, and excellent communication skills. You’ll ensure data quality and provide actionable insights to enhance business operations.

QUALIFICATIONS

  • Minimum of 5 years of experience in data engineering, analytics, or a related role, ideally within the hospitality industry..
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.

How To Apply:

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Responsibilities
  • Collaborate with various departments to identify data sources, key fields and their use. Then work with the Data Services team to brief in requirements for consumption.
  • Design and implement data models that support efficient data storage, retrieval, analysis and activation for the purpose of Analytics.
  • Develop and deploy data science models to support business operations and decision-making processes.
  • Work closely with Gaming, F&B, Hotels, Conferences, and Customer analytics teams to understand their data needs and provide actionable insights.
  • Work closely with Gaming product, Play Safe (RG), Financial Crimes (AML) and other business units to understand their strategy, what data can be collected and for what applications it can be used for.
  • Utilise various data models, to build a prototype output for the business to consume, including but not limited to forecasting, predictions and alerting.
  • Ensure the accuracy, completeness, and reliability of data through rigorous testing and validation.
  • Stay updated with the latest industry trends and technologies to continuously enhance data processes and models.
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