Data Scientist/Developer (Python/Energy)

Blunomy; Melbourne; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Blunomy is seeking a Data Scientist/Developer to join our Digital & Data team, working at the intersection of data analysis, modelling and software development.

You will organise complex energy and environmental datasets, apply statistical and ML techniques, and turn insights into reliable Python code and production tools solving real energy-sector decisions.

Qualifications

• Degree in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, or Engineering.
• Strong Python skills with experience handling data.
• Knowledge of statistical and machine-learning concepts and techniques.
• Understanding of software engineering principles and Git version control.
• Ability to work in a fast-paced, collaborative project-based environment.

Responsibilities

• Organise, clean, analyse and interpret complex energy and environmental datasets.
• Apply statistical, analytical and machine-learning techniques to identify patterns and practical solutions.
• Develop, validate and improve analytical and forecasting models.
• Translate models and analytical methods into clean, maintainable Python code.
• Build and improve data pipelines, APIs and digital tools.
• Contribute to software development, testing, code review and Git-based workflows.
• Collaborate with energy-sector specialists to turn analysis into client-ready solutions.
• Document methodologies, datasets and results clearly.
• Communicate technical findings to both technical and non-technical audiences.

Skills

Python

Statistics

Machine Learning

Git

Data engineering

APIs

Teamwork

Communication

Education

Data Science / Statistics / Mathematics / Computer Science / Engineering (quantitative)

Tools

Git

Job description

Blunomy is looking for a Data Scientist / Developer to join our growing Digital & Data team and work at the intersection of data analysis, modelling and software development.

This role is for someone who enjoys understanding and organising complex data, applying statistical and analytical methods, and then turning that work into reliable, maintainable Python code and digital solutions.

You’ll work with energy and environmental datasets, contribute to forecasting and analytical models, build data pipelines and APIs, and help develop production tools used to support real energy-sector decisions.

What you’ll do

• Organise, clean, analyse and interpret complex energy and environmental datasets.
• Apply statistical, analytical and machine-learning techniques to identify patterns, insights and practical solutions.
• Develop, validate and improve analytical and forecasting models.
• Translate models and analytical methods into clean, maintainable Python code.
• Build and improve data pipelines, APIs and digital tools.
• Contribute to software development, testing, code review and Git-based workflows.
• Work with Developers, Data Scientists, Consultants and energy-sector specialists to turn analysis into practical client and product solutions.
• Document methodologies, assumptions, datasets and results clearly.
• Contribute to client projects and communicate technical findings to both technical and non-technical audiences.

The role combines analytical thinking with software development, with a strong focus on ensuring that coding is underpinned by a sound understanding of the data, methodology and problem being solved. The role combines statistical analysis, data engineering and software-development responsibilities.

What we’re looking for

You’ll ideally have a degree or postgraduate qualification in Data Science, Statistics, Mathematics, Computer Science, Engineering or another relevant quantitative discipline, together with a strong interest in data analytics and problem-solving.

You’ll bring:

• Strong Python skills and experience working with data.
• Knowledge of statistical and machine-learning concepts and techniques.
• An understanding of software engineering principles and source control such as Git.
• Strong analytical and problem-solving capability.
• The ability to work collaboratively in a fast-paced, project-based environment.
• Good written and verbal communication skills.
• A genuine interest in energy, the environment, sustainability and the energy transition.
• Experience with cloud platforms such as GCP, Azure or AWS, data engineering, APIs, parallel computing or production software development would be advantageous.

Location: Sydney or Melbourne

Employment: Full-time, permanent

Working model: Hybrid – 3 days in the office / 2 days working from home

Blunomy is progressive in the adoption and integration of AI and emerging technologies. We encourage their thoughtful use to improve analysis, development and productivity, while recognising that AI supports rather than replaces the underlying knowledge, technical skills, critical thinking and professional judgement required for the role.