Modelling & Simulation (Science & Technology)
Analyze complex data sets to derive actionable insights and inform decision-making. Develop and maintain data pipelines and ETL processes for efficient data flow. Implement machine learning models to solve business problems and improve services. Collaborate with stakeholders to identify data requirements and translate them into technical specifications. Ensure data quality and integrity through rigorous testing and validation. Create data visualizations and reports to communicate findings effectively. Optimize database and data storage solutions for performance and scalability. Stay updated on emerging technologies and industry trends to recommend best practices. Provide support and troubleshooting for data-related issues. Participate in cross-functional teams to enhance data-driven strategies and initiatives. Desirable Program/Technical Abilities:
Programming Languages : Proficiency in Python and SQL; familiarity with R or Java is a plus. Data Analysis : Experience with data manipulation libraries (e.g., pandas, NumPy) and statistical analysis. Big Data Tools : Familiarity with Spark, Hadoop, or similar frameworks for handling large datasets. Data Visualization : Skills in Tableau, Power BI, or Matplotlib for creating clear and impactful visuals. Cloud Platforms : Basic understanding of AWS, Azure, or Google Cloud for data storage and processing. Machine Learning : Exposure to machine learning libraries (e.g., scikit-learn, TensorFlow) for building models. ETL Tools : Knowledge of ETL tools like Apache Airflow or Informatica to support data pipeline development. Database Management : Familiarity with relational (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB). Version Control : Experience with Git for collaborative coding and version tracking. Data Warehousing : Understanding of data warehousing solutions like Redshift or Snowflake. Main Duties
Analyze complex data sets to derive actionable insights and inform decision-making. Develop and maintain data pipelines and ETL processes for efficient data flow. Implement machine learning models to solve business problems and improve services. Collaborate with stakeholders to identify data requirements and translate them into technical specifications. Ensure data quality and integrity through rigorous testing and validation. Create data visualizations and reports to communicate findings effectively. Optimize database and data storage solutions for performance and scalability. Stay updated on emerging technologies and industry trends to recommend best practices. Provide support and troubleshooting for data-related issues. Participate in cross-functional teams to enhance data-driven strategies and initiatives. Minimum Requirements:
Australian Citizen (you must be a citizen to be considered for any APS roles). Baseline/NV1/NV2 Clearance (candidates with a clearance will be highly regarded). Federal Government experience. Is the above too intimidating? We'd still like to hear from you.
Are you a recent graduate or early-career professional looking to start your data journey? Learn from experienced data veterans as they pass on their knowledge while you as a Data Scientist or Data Engineer. If you're passionate about data and ready to make a difference, we encourage you to apply! We believe that a strong work ethic, paired with a passion for data, will drive your success.
At Randstad, we are passionate about providing equal employment opportunities and embracing diversity to the benefit of all. We actively encourage applications from any background.
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