Associate AI Analyst

Who we are?

Headquartered in Perth, Australia, with offices globally including in Colombo, Sri Lanka, Qoria is an ASX listed global leader in child digital safety technology and services. We are a purpose-driven business, operating under the ‘Linewize’ brand in North America and Asia Pacific, the ‘Smoothwall’ brand in the UK, ‘Qoria LK' in Sri Lanka and the ‘Qoria’ brand in EMEA. Our solutions are utilised by schools, school districts, and parental communities to protect children from seeing harmful content online, identify children at risk based on their digital behaviours and ensure teachers maintain focus and safe learning in the digital classroom. 30.000 schools and 7 million parents depend on our solutions to keep 25 million children safe in 180 countries around the world.

What’s the opportunity?
We are looking for a passionate and detail-oriented Associate – AI Analyst to join our team. This role involves working closely with internal and external stakeholders to transform business requirements into actionable insights through data analysis, visualization, and reporting. The ideal candidate should have a strong analytical mindset and a willingness to learn and grow in the field of business intelligence and AI analyst.

Key Responsibilities:

• Collaborate with end users and stakeholders to understand business problems and translate them into AI and analytical solutions.

• Translate functional requirements into technical specifications for model development and deployment.

• Design, build and maintain data pipelines and ETL processes to support model training and inference (feature engineering, data validation, dataset versioning).

• Perform exploratory data analysis and identify trends, patterns, and data quality issues that affect model performance.

• Support model prototyping and evaluation: run experiments, track metrics, and summarise results.

• Assist with basic MLOps activities (model versioning, monitoring, experiment tracking, CI/CD for models).

• Help containerize models (Docker) and prepare artefacts for deployment; collaborate with engineering for productionisation.

• Execute SQL queries and manipulate datasets to support modelling and decision-making.

• Create clear, user-friendly dashboards and reports to communicate model outputs and business insights.

• Document technical specifications, processes, and user guides; assist with user training and handovers.

• Identify opportunities to improve processes and product features using AI/ML approaches.
  

Requirements:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Information Systems, Engineering, or a related field.

• 1–2 years of experience in a data analytics, AI, BI or machine learning-adjacent role (internships and academic projects included).

• Experience with Python (data/ML libraries such as pandas, scikit-learn).

• Familiarity in SQL for querying relational databases.

• Practical experience or coursework in applied machine learning (classification, regression, basic model evaluation).

• Basic understanding of MLOps concepts (model lifecycle, monitoring, experiment tracking, CI/CD).

• Capability to understand and build data pipelines for AI models (ETL/feature engineering basics).

• Experience creating dashboards and reports for non-technical users (Power BI, Tableau, or similar).

• Strong analytical, problem-solving and data-wrangling skills.

• Excellent communication and presentation skills — ability to clearly articulate your thought process, modelling assumptions and trade-offs is a key factor for this role.

• Eager to learn, Team player mindset, and detail-oriented in a fast-moving environment.

Preferred Qualifications:

• Experience with Docker and containerising ML models.

• Familiarity with ML frameworks (TensorFlow, PyTorch) or higher-level tools for model training.

• Exposure to cloud platforms and services for ML (e.g.: GCP AI Platform).

• Experience with model monitoring, logging, or model governance practices.

• Prior client-facing experience or working with cross-functional teams.

If you are passionate about data and looking for an opportunity to work on impactful projects, apply now!