Data Analyst

Responsible for applying data analysis and quantitative methods to large and complex energy market datasets to support MFT Australia’s trading, forecasting, and market strategy activities.

The position focuses on collecting, analysing, and interpreting market and operational data from the Australian National Electricity Market (NEM) to generate insights that support decision‑making, forecasting accuracy, and commercial optimisation.

Benefits

• A competitive and entrepreneurial work environment
• Professional and committed colleagues with great ambitions
• The chance to one day become partner
• A modern workplace with an ambitious and professional culture

Task & responsibilities

• Gather, process, and analyse large datasets related to the Australian National Electricity Market (NEM), including price, demand, generation, bidding and network data.
• Conduct price forecasting simulations to assess market behaviour, evaluate scenario impacts, and support data-driven trading and risk management decisions.
• Develop and maintain data models, analytical tools, and dashboards to support energy trading, forecasting, and strategic planning.
• Apply statistical and quantitative analysis techniques to identify trends, patterns, risks, and opportunities within energy market data.
• Clean, validate, and structure raw data from multiple sources to ensure accuracy and reliability for downstream analysis and reporting.
• Translate complex datasets and analytical results into clear insights and visualisations to support commercial and operational decision‑making.
• Support forecasting models by providing data analysis, validation, and performance evaluation inputs.
• Collaborate closely with traders, analysts, and other stakeholders to ensure data outputs align with business needs and market realities.
• Interpret market and technical data relevant to the Australian energy market and integrate this into ongoing analysis.
• Contribute to continuous improvement of data methodologies, analytical frameworks, and tooling used across the business.

Qualification & experience

Education:

• A Bachelor’s degree in a quantitative field (IT, Math, Statistics, or Business). Postgraduate certificates are also highly valued for career advancement.

Core Technical Skills:

• SQL: The non-negotiable industry standard for querying and extracting data from databases.
• Spreadsheets: Advanced Excel and Google Sheets for data cleaning and initial ad-hoc analysis.
• Programming: Proficiency in Python or R to manipulate large datasets and run statistical analyses.
• Visualization: Dashboarding tools like Tableau or Power BI to present complex findings as intuitive stories.

Soft Skills:

• Business strategy, data storytelling, and the ability to clearly translate complex metrics for non-technical stakeholders.