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Data Scientist

Perth, Western Australia, Australia

Actively hiring, first seen by us 1 day ago
Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Build ingestion pipelines from client systems like SCADA, asset registers and geospatial data

  • Develop layered data architectures with raw, staging and curated models using dbt

  • Build, validate and deploy statistical and machine learning models to production

  • Establish CI/CD, environments, secrets management and automation for data pipelines

  • Assess client data maturity, quality and governance and recommend improvements

From the employer’s posting
Design and build ingestion pipelines from client source systems including SCADA, asset registers, geospatial, climate, environmental and utilities data into cloud platforms
Develop robust, layered data architectures including raw, staging and curated data models using dbt or equivalent frameworks.
Build, validate and deploy statistical and machine learning models, transforming prototypes into monitored and production-ready solutions.
Establish CI/CD practices, environments, secrets management and automation for data and model pipelines.
Assess client data maturity, quality and governance practices, providing strategic recommendations for improved data collection and management.
Apply at WSP Global

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 4, 2026
Employer says posted
Oct 20, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 7 and day 55.

From 9,971 similar postings that came down. Coming down is not always a hire.

WSP Global is hiring

13 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • dbt
  • Docker
  • MLflow
  • Power BI
  • Snowflake
  • Terraform
  • Airflow
Where the posting names them
You will bring a combination of data science expertise and engineering rigour, including: - Strong Python development skills, including software engineering best practices such as packaging, testing, version control, code reviews and maintainable code design. - Advanced SQL skills with experience in optimisation, data modelling, metric development and complex transformations.
- Strong Python development skills, including software engineering best practices such as packaging, testing, version control, code reviews and maintainable code design. - Advanced SQL skills with experience in optimisation, data modelling, metric development and complex transformations. - Production experience with cloud data platforms such as Snowflake, Databricks, Azure Data Services or equivalent AWS technologies.
- Advanced SQL skills with experience in optimisation, data modelling, metric development and complex transformations. - Production experience with cloud data platforms such as Snowflake, Databricks, Azure Data Services or equivalent AWS technologies. - Experience with modern transformation and orchestration tools including dbt, Airflow, Azure Data Factory or similar.
You will: - Design and build ingestion pipelines from client source systems including SCADA, asset registers, geospatial, climate, environmental and utilities data into cloud platforms such as Snowflake, Databricks and Azure. - Develop robust, layered data architectures including raw, staging and curated data models using dbt or equivalent frameworks.
- Production experience with cloud data platforms such as Snowflake, Databricks, Azure Data Services or equivalent AWS technologies. - Experience with modern transformation and orchestration tools including dbt, Airflow, Azure Data Factory or similar. - A solid understanding of statistics and machine learning techniques including regression, classification, forecasting and validation methodologies.
- MLOps tooling including MLflow, model registries and model monitoring. - Docker, Azure Functions or other deployment technologies. - Infrastructure as Code tools such as Terraform or Bicep.
- Design and build ingestion pipelines from client source systems including SCADA, asset registers, geospatial, climate, environmental and utilities data into cloud platforms such as Snowflake, Databricks and Azure. - Develop robust, layered data architectures including raw, staging and curated data models using dbt or equivalent frameworks. - Build, validate and deploy statistical and machine learning models, transforming prototypes into monitored and production-ready solutions.
Experience in any of the following areas will be highly regarded: - MLOps tooling including MLflow, model registries and model monitoring. - Docker, Azure Functions or other deployment technologies.
- Optimisation, simulation or digital twin applications. - Power BI or similar visualisation tools sufficient to support analyst handover and reporting requirements. Why join WSP?
- Docker, Azure Functions or other deployment technologies. - Infrastructure as Code tools such as Terraform or Bicep. - High-frequency telemetry, IoT or time-series data.

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About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Data Scientist

At WSP, we're using data to help solve some of the world's most complex infrastructure, environmental and community challenges. From utilities and transport networks to climate resilience and asset management, our teams are delivering intelligent solutions that create lasting impact.

We're looking for a Data Scientist with strong data engineering capabilities who can take projects from raw source systems through to production-ready data products and machine learning solutions. This is not a research-focused role. We're seeking someone who enjoys building end-to-end solutions, owns the technical delivery, and can bridge the gap between data engineering, analytics and operationalised AI.

What you'll do

As part of our growing Data & Digital team, you'll design, build and deploy scalable data and machine learning solutions for a diverse range of infrastructure clients.

You will:

  • Design and build ingestion pipelines from client source systems including SCADA, asset registers, geospatial, climate, environmental and utilities data into cloud platforms such as Snowflake, Databricks and Azure.
  • Develop robust, layered data architectures including raw, staging and curated data models using dbt or equivalent frameworks.
  • Build, validate and deploy statistical and machine learning models, transforming prototypes into monitored and production-ready solutions.
  • Establish CI/CD practices, environments, secrets management and automation for data and model pipelines.
  • Assess client data maturity, quality and governance practices, providing strategic recommendations for improved data collection and management.
  • Deliver end-to-end projects, including discovery, architecture design, development, testing, deployment, documentation and client handover.
  • Support business development activities through technical input into proposals, bids and advisory engagements.
  • Collaborate with multidisciplinary teams across transport, water, energy, defence, environment and major infrastructure projects.
     

What we'll be looking for
Essential

You will bring a combination of data science expertise and engineering rigour, including:

  • Strong Python development skills, including software engineering best practices such as packaging, testing, version control, code reviews and maintainable code design.
  • Advanced SQL skills with experience in optimisation, data modelling, metric development and complex transformations.
  • Production experience with cloud data platforms such as Snowflake, Databricks, Azure Data Services or equivalent AWS technologies.
  • Experience with modern transformation and orchestration tools including dbt, Airflow, Azure Data Factory or similar.
  • A solid understanding of statistics and machine learning techniques including regression, classification, forecasting and validation methodologies.
  • Demonstrated experience operationalising data products, machine learning models or data pipelines within production environments.
  • Experience working with large, complex and imperfect operational datasets from multiple source systems.
  • Strong stakeholder engagement skills, with the ability to communicate technical concepts and architectural decisions to both technical and non-technical audiences.
     

Desirable

Experience in any of the following areas will be highly regarded:

  • MLOps tooling including MLflow, model registries and model monitoring.
  • Docker, Azure Functions or other deployment technologies.
  • Infrastructure as Code tools such as Terraform or Bicep.
  • High-frequency telemetry, IoT or time-series data.
  • Geospatial analytics and tools such as GeoPandas.
  • Infrastructure sector experience across water, transport, energy, defence or environmental services.
  • Optimisation, simulation or digital twin applications.
  • Power BI or similar visualisation tools sufficient to support analyst handover and reporting requirements.
     

Why join WSP?

At WSP, you'll work on projects that shape cities, communities and critical infrastructure across Australia and beyond. You'll join a collaborative team of engineers, scientists, consultants and digital specialists who are passionate about solving complex problems with data and technology.

We offer:

  • The opportunity to work on nationally significant infrastructure and sustainability projects.
  • Access to industry-leading digital, AI and cloud technologies.
  • Flexible working arrangements that support work-life balance.
  • Ongoing investment in learning, development and technical career growth.
  • A collaborative, inclusive and high-performing culture where innovation is encouraged.
  • The chance to influence how data and AI are applied to some of the world's most pressing challenges.

 

Imagine a better future for us all and a better future for you.

With us, you can. Apply today.

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Perth, Western Australia, Australia

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