Data Scientist, Sydney
2 weeks ago
About our team
What did you have for breakfast today? Whether it’s the flour in your toast or the grain in your cereal, it’s highly likely that GrainCorp helped get it onto your plate As we find new ways to connect rural communities with food, animal feed and industrial customers around the world, we are proud to say we’re leading the way in sustainable agriculture.
About the role
Join our dynamic Advanced Analytics team as a Junior Data Scientist and support the delivery of high impact data science use cases. This varied role involves:
• Business engagement: capability to understand business problems and discover data science initiatives.
• Deep data analysis and experiments: capability to drive new data science initiatives from deeper data analysis and experiments.
• Model build and deployment: capability to implement and build machine learning models to address business problems.
• Cross-functional Collaboration: capability to collaborate effectively with other team members, including product owner, data scientists, data engineers and business/data SME to deliver cohesive solutions that meet business objectives.
• Quality of Code: capability to write and review high quality code to ensure coding standards, readability, maintainability, and efficiency.
About your experience
• Industry experience in Agriculture, Supply Chain or Manufacturing is highly desirable
• STEM degree (PhD preferred)
• Machine Learning and Statistical Modelling: Hands-on experience in developing and implementing various machine learning models and statistical techniques, such as regression, clustering, and time series analysis.
• Programming and Data Manipulation: Proficiency in programming languages, primarily Python, and experience in data manipulation using libraries such as Pandas, NumPy, and data visualization tools.
• Big Data Technologies: Experience working with big data technologies such as Apache Spark, Hadoop, and knowledge of SQL for extracting and manipulating large datasets.
• Cloud Computing: Experience working with Azure cloud platform, familiarity with cloud-based data science tools and services.
• Domain Knowledge and Problem Solving: Experience in applying data science to solve real-world business problems, with a strong ability to understand domain-specific data and business processes.
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