Senior Data Scientist

at  Cricket Australia

Working for Cricket Australia means that you become a part of Australia’s proud history and help us look toward the future. We are seeking to drive bold, transformative change in digital experiences, junior participation, culturally diverse inclusion, gender equality and sustainability, whilst also reimagining the W/BBL, building player connection through storytelling and playing our part in developing the game globally.
Our purpose is clear; to unite and inspire everyone to love and play cricket. Cricket is so much more than just a game; it brings people together and binds us all through our shared experiences.
This is your opportunity to join a purpose led organisation that truly makes a difference to Australians.

WHO WE ARE LOOKING FOR

• 5+ years experience in data science related fields
• Relevant tertiary qualifications: Bachelor or post graduate degree in Statistics, Applied Mathematics, Data Science, or related
• Expertise in customer profiling, predictive modelling
• Proficiency in Python and/or R; and competency in SQL
• Demonstrated experience in applying best practice within a cloud data environment, Azure experience desirable
• Understanding of data privacy frameworks and the ethical handling of personal data
• Excellent communication and interpersonal skills, with the ability to work effectively in a collaborative team environment

This is an exciting time for us, as we have created a brand-new Senior Data Scientist role within our Digital, Marketing, & Communication department. As the Senior Data Scientist in the Audience Growth and Analytics Team you will leverage data to drive user acquisition, retention, and engagement. By analysing customer behaviour, building predictive models, and implementing A/B testing methodologies, you will enable and empower cross functional teams to deliver personalised experiences and optimised marketing efforts.

Reporting to the Head of Audience Growth and Analytics, you’ll be responsible for:

• Developing, refining, and implementing audience segmentation models to improve understanding of our customer base, and enable personalised engagement;
• Building and maintaining predictive models to forecast user growth, churn, and lifetime value;
• Implementing machine learning techniques to predict customer behaviours and optimise growth strategies;
• Conducting thorough deep dive analyses to understand audience behaviours and engagement.