Energy markets · Data & statistical analysis
Senior Data & Statistical Analyst
I'm Carol Tran, data analyst and mom of two. For over nine years at the Australian Energy Council I've analysed wholesale pricing, demand and emissions across the NEM and WEM, and built regression and scenario models in Python, SQL and Power BI to forecast rooftop solar and battery adoption. Eight years of sales and data analytics at an anime retail store added the commercial side: pricing, forecasting and customer behaviour. I care about an energy transition that keeps electricity affordable.
Experience
Energy markets since 2016, retail analytics and research before that.
- Energy market analytics & forecasting: analyse wholesale pricing, generation performance, electricity demand, emissions and renewable energy trends across the NEM and WEM; apply regression modelling and scenario analysis to forecast rooftop solar and battery adoption, and track renewable curtailment for the Energy 2050 project.
- Data science & automation: use Python, SQL, Power BI and advanced Excel to consolidate multi-source datasets, build dashboards, and develop the automated reporting pipelines behind Electricity Gas Australia, the AEC Quarterly Solar Report and Coal NPI, with strong data validation controls.
- Commercial & policy analytics: conduct scenario modelling on membership pricing structures, retail market behaviour and customer affordability issues, supporting strategic and commercial decision-making.
- Benchmarking & stakeholder reporting: produce industry benchmarking reports, including Generation Performance Benchmarking and OH&S Benchmarking, applying statistical analysis to confidential operational datasets from major energy companies.
- Communication & industry insights: translate complex analytical findings into clear recommendations for executives, policy teams and industry stakeholders; as secretariat of the OH&S Working Group, present proposed indicators to 12 industry representatives.
- Commercial & customer analytics: analysed sales, purchasing behaviour, retention trends, AUD/JPY movements and competitor pricing across 4,200+ customers and ~1,900 SKUs; identified an 80% reduction in customer acquisition cost by shifting from Google Ads to eBay while maintaining sales volume.
- Demand forecasting: forecast convention attendance and product demand using historical sales, social media engagement and guest line-ups, enabling accurate inventory planning and eliminating overstock and stock shortages during peak periods.
- Revenue & pricing optimisation: introduced a 25% pre-order deposit model during 2020–21 supply chain disruptions, contributing to 30% average year-on-year sales growth; recommended a packaging restructure that increased shelf capacity fivefold and grew convention revenue by 20%.
- Shipping cost optimisation: built a packaging and shipping optimisation model using product dimensions, box sizes and freight pricing rules to minimise costs while protecting margin and expanding regional sales.
- Dashboards & reporting: built Power BI dashboards tracking conversion rates, retention, inventory turnover, website traffic and sales performance for ongoing KPI monitoring and operational decisions.
- Filtered, analysed and summarised genetic datasets in R and Excel for cancer mutation research.
- Contributed to a poster on amplicon-based targeted sequencing for inherited sarcoma risk factors.
Projects
Case studies in machine learning and retail analytics.
Analysis and Retention Planning on Customers Leaving an Energy Retailer
The client blamed price rises and had a 20% discount ready. The data said otherwise: the discount would have lost €506k a year, and the strongest churn signal is relationship age, not price.
Read the case study→
Evidence from 1,869 Exit Interviews: Why Customers Left
Most churn analyses guess at motive. Here nobody has to: all 1,869 leavers have a recorded reason, price ranks fourth, and the most common answer is the attitude of one support person.
Read the case study→
Writing
Analysis published on energycouncil.com.au.
Australia's Home Battery Surge: A Question of Equity
Postcode-level SEIFA analysis of who the federal battery rebate is reaching, state by state.
Read the article
OECD Price Comparison: How Do We Stack Up?
Australia's electricity prices against the OECD, nominal and cost-of-living adjusted.
Read the article
Solar Report: Second Quarter 2025
Quarterly snapshot of rooftop solar: capacity, payback periods, and LCOE.
Read the articleSkills & Domain Knowledge
Over nine years of energy market and retail analysis, presented to executives and industry stakeholders.
BI & Visualisation
Query & Databases
Languages
Spreadsheets
Domain knowledge
Certifications
Education
Bachelor of Science (Statistics and Stochastic Processes), University of Melbourne, 2012–2014. Specialised in probability theory, stochastic processes, statistical inference, quantitative modelling and predictive analysis, providing a strong foundation for machine learning and forecasting.
Get in touch
Open to senior data roles in energy, utilities, and policy.
Melbourne-based, on-site or remote. Email is the fastest way to reach me.