Data Scientist

WSP USA; Sydney; On-site; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible working

Career growth

Tech training

Job summary

WSP USA in Sydney seeks a Data Scientist to design and deliver end-to-end data and AI solutions for infrastructure clients. You will bridge data engineering, analytics and operations, taking projects from raw sources to production-ready data products and ML models.

The role emphasizes end-to-end delivery, CI/CD practices, scalable architectures, and collaboration with multidisciplinary teams across transport, water, energy and environment. Flexible working is available.

Qualifications

• Combination of data science and engineering rigor.
• Experience building production data products and ML models.
• Strong Python development with testing and version control.
• Advanced SQL and data modelling for analytics.
• Experience with cloud platforms (Snowflake, Databricks, Azure).
• Proven ability to deliver end-to-end data projects from discovery to handover.

Responsibilities

• Design and build ingestion pipelines from client source systems into cloud platforms.
• Develop layered data architectures with raw, staging, and curated models.
• Build, validate, and deploy ML models in production environments.
• Establish CI/CD, secrets management, and automation for data pipelines.
• Assess data maturity and governance, providing strategic recommendations.
• Deliver end-to-end projects including discovery, architecture, development, testing, and client handover.
• Support business development with technical input for proposals.

Skills

Python development

Advanced SQL

Cloud data platforms

dbt / Airflow

Statistics / ML

Production ML systems

Data governance

Stakeholder engagement

Tools

Snowflake

Databricks

Azure Data Services

dbt

Job description

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.