Category: Development and implementation

Subcategory: Data and analytics

Machine learning - MLNG

Developing systems that learn from data and experience, improving performance, accuracy and adaptability in dynamic environments.

Levels:

Level 2:
Description: Assists in data preparation, model training and evaluation tasks under routine supervision. Uses standard machine learning frameworks and tools to develop basic models for well-defined problems. Documents results and contributes to maintaining machine learning solutions.

Level 3:
Description: Applies established machine learning techniques and algorithms to solve business problems. Selects and prepares data for model training and evaluation. Trains, optimises and validates machine learning models using standard tools and frameworks. Deploys models into production and monitors their performance. Communicates results and limitations to stakeholders.

Level 4:
Description: Assesses the suitability of machine learning and designs and develops solutions for a range of business problems. Selects and applies appropriate techniques and algorithms based on data characteristics and business requirements. Provides guidance to others. Engineers features and optimises model performance. Implements algorithms and contributes to development, evaluation, monitoring and deployment. Applies industry-specific rules and guidelines, anticipating risks and implications. Collaborates with cross-functional teams to integrate machine learning models into production systems. Conducts in-depth performance analysis and troubleshoots issues.

Level 5:
Description: Leads the development and implementation of machine learning solutions for complex, high-impact business problems. Architects end-to-end machine learning pipelines and systems, incorporating MLOps practices. Evaluates and selects tools, frameworks and infrastructure for machine learning projects. Establishes practices and standards for machine learning development and operations. Provides expert advice and guidance on machine learning techniques and applications. Collaborates with stakeholders to align machine learning initiatives with organisational goals.

Level 6:
Description: Sets the strategic direction and roadmap for machine learning adoption and innovation within the organisation. Establishes governance frameworks and recommended protocols for responsible, ethical and sustainable development and use of machine learning. Leads the development of organisational capabilities, policies, standards and guidelines in machine learning. Collaborates with senior stakeholders to identify high-impact opportunities for machine learning and drives their implementation. Follows research and industry trends and integrates them into organisational practices.