Data Scientist

In Schneider Electric, everything we do is geared towards advancing progress and sustainability for all-our colleagues, customers, partners, and the communities and societies we serve.

Whether it's through our products, software, and services that propel the digital transformation of energy management and automation, or through our corporate citizenship and volunteer activities, we make a meaningful impact by empowering people and organizations to become more resilient, electric, and digital.

Which is where you come in.

Working at Schneider Electric means working toward a cleaner, better world.

You're part of a global team built on inclusion, mastery, purpose, action, curiosity, and teamwork, turning sustainability ambitions into actions.

The Role: Data Scientist

We are seeking a Data Scientist to partner with our Global Supply Chain teams to improve operational and planning decisions through forecasting, optimisation, predictive analytics, and automation.

In this role, you will develop and deploy data science solutions across demand planning, supply planning, inventory, and related functions.

Working closely with business stakeholders, you will take solutions from concept to production, ensuring they are effectively embedded into operational workflows and continuously improved.

Based in Macquarie Park, Sydney, with opportunities for candidates in Adelaide, Brisbane, or Auckland, this is an exciting opportunity to apply advanced analytics to complex supply chain challenges and deliver measurable business outcomes.

What will you do?



* Partner with Global Supply Chain stakeholders to identify opportunities to improve, support, or responsibly automate decisions, processes, and existing models.


* Translate business challenges into practical analytical solutions that deliver measurable outcomes.


* Design and develop forecasting, optimisation, predictive, and prescriptive analytics solutions.


* Own the end-to-end data science lifecycle, from exploration and development through to validation, productionisation, monitoring, and continuous improvement.


* Deploy solutions using governed enterprise infrastructure and integrate them into operational workflows.


* Evaluate solution performance, adoption, and business impact, ensuring ongoing value creation.


* Explore opportunities to leverage AI-enabled reporting, automated insights, and decision-support capabilities.

Key Responsibilities


* Collaborate with Data Architecture and Platform teams to productionise solutions using enterprise AWS infrastructure and established technical standards.


* Monitor, maintain, and enhance deployed models and analytical solutions.


* Document model methodologies, assumptions, limitations, dependencies, and operational requirements.


* Communicate findings, risks, recommendations, and limitations clearly to both technical and non-technical audiences.


* Contribute to use-case prioritisation, backlog refinemen...