Energy Transition Specialist

2 weeks ago

Haymarket, New South Wales, Australia beBeeData Full time $80,000 - $120,000

Transforming the energy landscape requires more than just data – it demands a bold vision, technical expertise, and a relentless drive to innovate.

As a key member of our platform team, you'll play a pivotal role in shaping the future of clean energy. Your work will be at the heart of our system, building models, analytics, and insights that power real-time control, customer optimisation, and operational intelligence.

Working closely with software engineers, product owners, and domain experts, you'll develop and deploy cutting-edge models that interpret telemetry, forecast performance, and orchestrate system efficiency.

This is a hands-on opportunity in a fast-paced environment where you'll design experiments, prototype algorithms, work with large datasets, and bring your ideas into production through collaboration with our platform and data engineering teams.

We're looking for individuals who thrive in high-trust, high-ownership environments where clarity, focus, and meaningful outcomes take precedence over reports.

The Role:

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.

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