Data Scientist

Easygo

Easygo, based in Melbourne, is a notable service provider in the iGaming industry, partnering with brands like Stake.com and Kick.com. As the company continues to expand, they offer a vibrant work environment inviting talent from various fields such as Tech and Marketing. The Data Scientist role plays a crucial part in delivering innovative data science projects globally, positively impacting millions of users.

In this role you can expect to have the responsibilities:

• Design and implement comprehensive machine learning solutions for key business challenges
• Develop strategies for data collection from global sources
• Collaborate with diverse teams to identify and prioritize impactful data science opportunities
• Build and deploy scalable ML models for large-scale data processing
• Present insights and recommendations to stakeholders
• Contribute to the creation of best practices for ML model development and deployment

This role comes with the following benefits:

• EAP access for family
• Access to 9,000+ courses on Learning and Development Platform
• Paid volunteer day
• Free coffee and beverages
• Free catered breakfast
• On-site massages
• Team lunches and happy hours
• Fun office environment with games and consoles
• Stocked snack and drink areas

This role requires you to have:

• 2+ years in data science
• Bachelor's degree in relevant quantitative field
• Strong Python programming skills
• Proficient in SQL
• Understanding of machine learning algorithms
• Experience with cloud platforms and distributed computing

You would benefit from having:

• Master's or PhD in quantitative disciplines
• Experience with AWS and ML deployment pipelines
• Track record in managing ML lifecycle for large data projects
• Expertise in NLP or Computer Vision
• Experience with deep learning frameworks like PyTorch
• Handling big data technologies

Easygo commits to a work environment that values diverse contributions and provides an equal opportunity for all to succeed, ensuring a discrimination-free workplace based on merit and accomplishment.