Company: Talent World on behalf of Ayla Solutions Pty Ltd
Location: Perth, WA
Position Title: Data Scientist
Employment Type: Full-time, Permanent
Salary: $100,000 – $120,000 per annum plus superannuation

About Us:
Ayla Solutions is a Perth-based data and analytics consultancy. We help organisations across mining and resources, utilities, health, education and local government turn their data into better decisions, through data strategy and governance, data engineering, analytics, and artificial intelligence and machine learning solutions.

About the Role:
We are looking for a Data Scientist to join our growing AI and machine learning team. You will apply statistical and machine learning techniques to large, complex datasets to build models that help our clients plan and make decisions, and take those models from first prototype through to production on cloud platforms.

The role combines hands-on technical delivery with direct client engagement, and offers the chance to help shape Ayla’s AI and machine learning practice as it grows.

Key Duties and Responsibilities:

- Work with clients and internal stakeholders to define business problems that can be solved with data science and machine learning, and agree the scope, objectives and success measures of each analytical engagement.
- Specify the data required for each initiative, identify relevant sources across enterprise, operational and cloud systems, and design the methodology for collecting, preparing and analysing it.
- Assess source data for completeness, accuracy, consistency and bias, and document its reliability, limitations and fitness for use before it is relied on in models or reporting.
- Mine, profile and cleanse large structured and unstructured datasets,



including documents and images, to uncover the trends, anomalies and patterns that generate business insight.
- Analyse and interpret complex datasets using statistical methods, producing statistics that describe current performance and infer future trends across areas such as safety, compliance and production.
- Formulate predictive, forecasting and simulation models of business and operational processes, such as production forecasting to support planning decisions.
- Develop advanced algorithms using numerical, statistical and machine learning techniques, including computer vision, natural language processing and large language model approaches.
- Test models against real-world observations, monitor accuracy and drift once in production, and tune, retrain or rebuild models as data and business conditions change.
- Build and deploy end-to-end machine learning solutions on cloud platforms such as AWS and Azure, using containerisation and serverless services, and applying MLOps practices for versioning, monitoring and retraining.
- Expose machine learning models to business applications and downstream processes through REST APIs, so that predictions and extracted data can be used in day-to-day operations.
- Design and maintain the data pipelines that feed model training and inference, including ETL workflows into cloud data warehouses such as Snowflake.




- Translate model results and analytical findings into clear reports, visualisations and recommendations that support management’s strategic planning and decision-making.
- Document models, methodologies, assumptions and code to support reproducibility, governance and handover to client teams.
- Evaluate emerging AI and machine learning tools, frameworks and methods, and recommend how Ayla’s AI and machine learning practice should adopt them.
- Mentor junior data scientists and interns, review their work, and contribute to building Ayla’s AI and machine learning capability.

Skills and Experience Required:

- Bachelor degree or higher in data science, statistics, mathematics, computer science, artificial intelligence or a related field.
- At least two years’ experience in a data science, machine learning or related role.
- Strong programming skills in Python and SQL, including machine learning libraries such as scikit-learn, PyTorch or TensorFlow.
- Experience building statistical, forecasting or machine learning models and deploying them into production on a cloud platform such as AWS or Azure.
- Experience working with large datasets and cloud data platforms such as Snowflake.
- Ability to explain technical findings clearly to non-technical stakeholders.

Desirable:

- Experience with computer vision, natural language processing or large language models.
- Experience with Docker, serverless services (AWS Lambda, Step Functions) and MLOps practices.
- A cloud machine learning certification, such as AWS Certified Machine Learning Engineer.
- Consulting or client-facing project experience.
- Experience with enterprise systems such as SAP SuccessFactors.

📌 Data Scientist (Perth)
🏢 Talent World
📍 Perth