Data Scientist

Overview NRN is revolutionising how Aussies use energy. With a 2030 goal to outfit 250,000 homes with solar and battery setups, NRN is leading a sustainable, wallet-friendly energy movement. Our model enables customers to save without upfront costs or complex finance deals, supported by a network of Energy Retailers and Solar Retail Partners (SRPs). NRN is a positive, diverse culture focused on transparency and high performance. Headquartered in Circular Quay, our team thrives on purpose, high performance, and care for each other and the mission.
Our team builds real-world infrastructure and smart systems that enable cleaner, smarter energy outcomes. Join us at the intersection of data, engineering, and climate impact to help shape the future of Australia's energy landscape.
The Role The Role: As a Data Scientist at NRN, you'll work at the heart of our energy platform, building the models, analytics, and insights that power system control, customer optimisation, and operational intelligence.
You'll work closely with software engineers, product owners, and domain experts to develop and deploy models that drive everything from real-time telemetry interpretation to forecasting, device performance analysis, and system orchestration.
This is a hands-on role in a fast-moving environment—you'll be designing experiments, prototyping algorithms, working with large datasets, and bringing models into production through close collaboration with our platform and data engineering teams.
You'll be joining a high-trust, high-ownership environment. We care deeply about clarity, focus, and delivering meaningful outcomes—not reports for their own sake.
Key Responsibilities Develop, train, and validate models to support real-time analysis, control logic, performance forecasting, and system efficiency.
Work closely with engineers to implement production-ready code and pipelines using clean, scalable methods.
Analyse time-series and telemetry data from solar, battery, and meter devices to extract system insights and inform product logic.
Build tools to surface actionable insights for internal stakeholders: system health, alerts, diagnostics, energy use patterns.
Collaborate with product, engineering, and operations teams to translate complex questions into data-driven answers.
Design and monitor data quality systems and anomaly detection pipelines to ensure platform reliability.
Support modelling of system contribution to energy savings, retailer benefits, and operational cost reduction.
Requirements 3–6 years of experience as a Data Scientist, preferably working with real-world systems or infrastructure.
Strong proficiency in Python (pandas, scikit-learn, NumPy, etc.) and SQL for exploratory and production use.
Experience working with time-series datasets and real-time or high-frequency data.
Ability to design and evaluate machine learning models for forecasting, classification, and anomaly detection.
Experience working cross-functionally with software engineers and product teams.
Familiarity with cloud-native data tooling—ideally GCP (BigQuery, Pub/Sub, Cloud Functions).
Comfortable with ambiguity and iteration—able to explore, validate, and refine rapidly.
Must be based in Australia, with preference for Sydney-based candidates available for hybrid work.
Nice to Have Hands-on experience with GCP services
Familiarity with Salesforce data models and working with Salesforce APIs
Why Join Us Tackle real, impactful problems in the clean energy transition.
Join a high-performing and supportive team with deep domain expertise.
Competitive salary and career growth in a fast-growing company.
Note: No recruiters please.
#J-18808-Ljbffr