Data Scientist/Developer

The Data Scientist / Developer applies their academic training, analytical capability and interest in the organisation and interpretation of data to the development of Blunomy's data and digital solutions.

The role combines data science, analysis and software development. It is responsible for understanding and working with complex energy and environmental datasets; applying appropriate statistical, analytical and modelling techniques; and translating those methods and insights into reliable, maintainable Python code, data pipelines and digital tools. A key focus of the position is ensuring that development is underpinned by a sound understanding of the data, methodology and analytical problem being addressed, rather than coding in isolation.

Working as part of Blunomy's Data & Digital team, the Data Scientist / Developer contributes to client projects and Blunomy products, collaborating with Developers, Senior Developers, Managers, consultants and energy-sector specialists to turn data and analysis into practical solutions.

The role is naturally curious about data, enjoys understanding how and why patterns occur, and wants to develop their capability at the intersection of data science, software development and the energy transition.

At Blunomy we are a small team that is flexible and enjoys the diversity of their role and the range of projects that they support. The breadth of the role includes:

Data Analysis & Modelling

• Understand project questions and determine the data and analytical requirements needed to address them.

• Source, organise, clean, transform and analyse energy, environmental and related datasets.

• Apply appropriate statistical, analytical and machine-learning techniques to identify patterns, relationships and insights.

• Develop, test and improve analytical and forecasting models.

• Assess data quality, completeness and limitations and understand their implications for analysis and model outputs.

• Validate analytical approaches and results and clearly document assumptions, methodologies and limitations.

• Use critical thinking and subject knowledge to interrogate results rather than relying solely on automated outputs

Development of Data Solutions

• Translate analytical methods and models into clean, reliable and maintainable Python code.

• Contribute to the development and improvement of Blunomy applications, digital products and client solutions.

• Build and maintain data processing workflows, pipelines and APIs that support analytical models and software products.

• Integrate data science outputs into production-ready software in collaboration with Developers and Senior Developers.

• Develop solutions that are scalable, reproducible and suitable for continued use beyond an individual analysis or project.

• Diagnose and resolve data, modelling and coding issues as they arise.

Project Support

• Support simple to moderately complex projects and contribute to work packages of complex projects, under the supervision of Managers or Principals.

• Prepare analysis and results to assist Managers or Principals in client presentations

• Assist in documenting methods, results, and datasets for internal and client use

• Contribute to testing, quality assurance, and version control (e.g., Git)

• Participate in actions/projects to assist the company in achieving greater efficiency, supervised by a manager or a principal.

Software Development

• Work within the team's agreed software-development practices, including source control, branching, pull requests, code review and testing.

• Write clear, efficient and appropriately documented code

• Participate constructively in peer code reviews and respond to feedback from more experienced Developers and technical leads.

• Contribute to improving the maintainability, consistency and reliability of Blunomy's codebase.

• Support testing, validation and quality assurance of analytical models and software outputs.

• Apply appropriate software engineering principles when moving analytical work from exploration into production environments.

Project Delivery & Problem Solving

• Deliver defined analyses, development tasks and project work packages within agreed scope, quality and timelines.

• Work with Managers and project leads to determine appropriate methodologies and practical approaches to client problems.

• Identify problems, investigate their underlying causes and develop evidence-based solutions.

• Prepare analysis, results, visualisations and supporting material for project and client outputs.

• Maintain appropriate documentation of datasets, analytical methods, assumptions and development work.

• Contribute to the continuous improvement of internal tools, methods and ways of working

• Collaboration & Knowledge Sharing

• Work collaboratively with Data Scientists, Developers, Senior Developers, Managers, consultants and subject-matter experts.

• Participate actively in project discussions, technical reviews and team learning sessions.

• Share analytical approaches, coding knowledge, lessons learned and useful techniques with other members of the team.

• Contribute technical and methodological input to proposals where appropriate.

• Seek technical guidance where appropriate and progressively build independence as experience develops.

• Communicate complex analytical or technical concepts clearly to demonstrate Blunomy's professional behaviours and values

Preferred experience

• Completed a degree or a postgraduate qualification in a relevant discipline such as Data Science, Statistics, Mathematics, Computer Science, Engineering or another relevant quantitative discipline.

• Passion for energy, environment and/or sustainable development

• A strong interest in working with data - including organising, interrogating, interpreting and drawing meaningful conclusions from complex datasets.

• Ability to think critically about data quality, methodology, assumptions and results rather than treating analysis as a purely technical process.

• Knowledge of statistical and machine learning concepts and algorithms

Experience with the data science tool kit:

• Python or R

• Source control (such as Git)

• Software engineering and app development skills

• Knowledge of cloud computing (such as Azure, GCP, AWS) is a plus

• Parallel computing (such as Spark or Dask) is a plus

Developer tool kit:

• Good oral and written communication

• An ability to work to project timelines

• Strong analytical and problem-solving skills

• Open to learning and appropriately integrating AI-enabled tools into their work, while applying professional judgement, critical thinking and appropriate validation of outputs

• Ability to work collaboratively in a fast-paced, project-based environment.

• Fluent in English

Why work for Blunomy?

You will be joining a passionate group of professionals, aligned in our mission. At Blunomy you are more than a 'cog in the machine', you will have the ability to make a real and lasting impact across the business. We are focused on finding the right people to journey with us, and to those who do, we offer:

• Working with a team who have diverse skills, expertise and are purpose driven

• Competitive remuneration

• Ability to participate in the company bonus scheme

• Hybrid working environment and offices based in either Melbourne or Sydney

• Ability to be part of a global team sharing knowledge and expertise

• Ongoing learning and development opportunities

• Weekly team lunch/breakfast

• Access to our Employee Assistance Program to support your well being

  Salary: Depending on experience

  Employment Type: Full time starting ASAP

Recruitment process

We put a lot of time and effort into identifying the best candidate who will enjoy and thrive in the Blunomy team. To do this we have a recruitment and selection process that has a number of steps. As your application progresses you can expect the following:

1. Applications close on 29th October 2026.

2. Approx 60 minute online test - testing basic data analytic skills, as well as critical thinking, numerical reasoning and role relevant skills etc.

3. Phone screen for candidates whose testing results and CV are what we are looking for

4. Technical Interview - case study and interview to explore more about your technical skills including your approach to incorporating AI.

5. Behavioural interview to explore your fit with the team and some of the softer skills needed for success

6. 3rd interview if required