Data Scientist: End-to-End ML & Data Engineering

WSP Global Inc.; Western Australia; Hybrid; AUD 110,000 - 160,000; Full time

Benefits offered by this job

Flexible working arrangements

Learning and development

Access to digital AI and cloud tech

Job summary

WSP Global Inc. is seeking a Data Scientist to design and deploy end-to-end data and ML solutions for infrastructure clients.

You will build ingestion pipelines to cloud platforms like Snowflake and Databricks, create robust data architectures, and productionize models with CI/CD and data governance considerations. You will bridge data engineering, analytics and AI, collaborating across transport, water, energy and other major projects.

Qualifications

• Strong Python development with testing and version control.
• Advanced SQL with data modelling and complex transformations.
• Production experience on Snowflake/Databricks/Azure data services.
• Experience with dbt, Airflow and data orchestration tooling.
• Solid understanding of statistics and ML techniques.
• Experience deploying data products and ML models to production.
• Ability to handle large, complex datasets across sources.

Responsibilities

• Design, build and deploy scalable data and ML solutions for infrastructure clients.
• Ingest data from SCADA, asset registers, geospatial, climate and utilities data.
• Develop robust data architectures with raw, staging and curated models.
• Establish CI/CD, secrets management and automation for pipelines.
• Support business development with technical input to proposals and bids.

Skills

Python development

Advanced SQL

Cloud platforms

dbt

Airflow

Statistics knowledge

Production data

Stakeholder comms

Tools

Snowflake

Databricks

Azure

Airflow

dbt

Terraform

GeoPandas

Power BI

Job description

WSP Global Inc. is seeking a Data Scientist to design and deploy end-to-end data and ML solutions for infrastructure clients.

You will build ingestion pipelines to cloud platforms like Snowflake and Databricks, create robust data architectures, and productionize models with CI/CD and data governance considerations. You will bridge data engineering, analytics and AI, collaborating across transport, water, energy and other major projects.