Data Engineering

• Design and build data pipelines (supporting use of data).
• Include processes of data quality, monitoring, and resolution.
• Incorporate best practices of managing “big data” (i.e. high volume, high velocity, high variety).

Artificial Intelligence

• Build AI models.
• Incorporate best practices of “MLOps” for managing the lifecycle of models. E.g. data preparation, model training, feature selection, evaluation, model selection, deployment, monitoring, maintaining.

Business Intelligence

• Deliver actionable insights from data.
• Build insightful data visualisations to communicate findings effectively.

Requirements

Skill Requirements

• Excellent written and verbal communication skills.
• Clearly articulates ideas and thoughts.
• Active listening and the ability to understand complex requirements.
• Problem-solving mindset with a proactive approach.
• Capability to work independently and as part of a team.
• Self-motivated and professional demeanour.
• Commitment to self-development and continuous learning.
• Attention to detail and accuracy.
• Good prioritisation and organisation skills.

Qualifications and Experience

• Degree in Data Science, Statistics, Computer Science, or a related field.
• Experience with data, analysis and machine learning models using tools like Python, R, or similar.
• Experience with coding using Python (preferred) or similar.
• Experience with database querying using SQL.
• Experience with data engineering concepts.
• Experience with machine learning concepts and algorithms.