Where Analytics Careers Take Shape

• Confidently manipulates and gains insight from downloaded and remote data sets
• Chooses imputation methods intentionally
• Makes connections across data sets efficiently and effectively
• Carries out machine learning processes in a coded environment (R or Python)
• Works with feature engineering to improve outputs
• Demonstrates thorough understanding of deep learning frameworks and architectures either through practice or technical knowledge
• Demonstrates advanced understanding of mathematics, statistics, probability, pattern detection and algorithm construction relevant to the analytical process
• Uses SQL flexibly
• Works within emerging and sometimes complex data and AI regulatory frameworks

Knowledge and Analytics

• Works with a range of data structures on solutions to complex problems
• Flexibly identifies environments to host solutions
• Takes a systematic approach to data pipelines
• Identifies strategies to work with new technology

Governance and Professionalism

• Sets standards in the organisation for ethical data practices
• Acts with integrity above and beyond own regulatory and legal jurisdictions
• Constructively evaluates own work and peer work
• Consistently operates within industry standards of interoperability
• Actively promotes and implements sustainable product design

Communication

• Negotiates effectively
• Creates quality visuals
• Aligns to international standards of accessibility
• Works to open science research standards
• Builds effective external business relationships

Leadership

• Reliably contributes to company risk strategy
• Identifies and critically evaluates assumptions
• Empowers others beyond the organisation
• Monitors developments
• Contributes in a significant way to the organisation