Decision science
- Predictive modelling and forecasting
- Optimisation under constraints
- Scenario analysis and risk trade-offs
commercially useful, statistically suspicious
Tracy Guo Data Scientist
I turn messy business questions into models, forecasts, optimisation logic, and decisions people can actually use. Nine-plus years across aviation, energy, and infrastructure. Fluent in Python, SQL, stakeholder translation, and politely asking, "what are we optimising for, exactly?"
9+years analytics
3domains survived
∞scenarios modelled
0patience for vague KPIs
what I do
Commercial analytics
- Revenue, capacity, and utilisation decisions
- Stakeholder-friendly insights
- Business cases that survive meetings
Technical toolkit
PythonSQLR
SnowflakeGCPPower BI
TableauScikit-learn
where I've been useful
2021 - now
Senior Data Analyst Jetstar Airways / Commercial Strategy & Transformation
Built predictive, forecasting, and optimisation models for commercial and operational decisions: overbooking, network planning, engine capex, partnerships, risk, revenue, and all the fun places uncertainty likes to hide.
2020 - 2021
Spatial Consultant GHD Digital / Location Intelligence
Modelled critical infrastructure networks, disruption scenarios, and downstream risk. Basically: if something spills, breaks, blocks, or cascades, make the model explain what happens next.
2019 - 2020
Data Scientist AECOM / Commercial Advisory
Forecasted energy demand, clustered customer behaviour, and supported solar, battery, and infrastructure planning decisions with data-driven workflows.
selected quests
Overbooking optimisation
Balanced revenue upside against denied boarding risk using probabilistic modelling and mitigation logic. Aviation chaos, but with math and manners.
Aircraft engine capex
Large-scale optimisation with millions of variables and constraints for maintenance planning, cost, availability, and long-term fleet decisions.
Network connectivity
Modelled passenger connectivity, route-level commercial potential, and partnership upside to support growth decisions.
Energy demand forecasting
Forecasting, clustering, and scenario analysis for customer demand, solar, battery planning, and investment decisions.
Utility spill modelling
Graph-based sewer network modelling for risk response and operational planning. Glamour is optional; impact is not.
Education
Master of Digital Infrastructure Engineering, University of Melbourne. Bachelor of Science, University of Illinois Urbana-Champaign.