Data Science Projects

Over twenty years of experience in delivering data science projects and predictive analytics solutions,
that accelerate competitive advantage.

Data Science Project, Energy Load Forecasting

Data Science Pilot Project

Use Case: Energy Load Forecasting

Customer: Aurora Energy, Hobart

Business value: Accuracy of load forecasts, has the potential to improve the effectiveness of the wholesale hedging strategy through greater flexibility in market exposure and sharper hedging procurement. 

Scope: Develop automated load forecasting solution, which imports historical half hour customer account data, with functionality to modify parameters, and produce forecasts with confidence intervals.

Outcome: Delivered, short and long term forecasting solution, with a mean absolute percentage error (MAPE) of less than 6%.

Data Science Project, Predicting Customer Churn

Data Science Project

Use Case: Customer Analytics – Predicting Churn

Customer: Randstad Australia, Sydney

Business value: Reducing customer churn by a small percentage, can produce significant revenue gains.  

– Business analysis and engagement with stakeholders
– Data profiling and data preparation to support classification modelling and survival analysis
– Trained, tested and validated classification models, to determine accuracy

Outcome: Delivered predictive solution, with over 90% accuracy, that identifies customers with a high propensity to churn.

Financial Forecasting

Data Science Production Project

Use Case: Cash-flow Forecasting

Customer: Commonwealth Bank – Daily IQ Project, Sydney

Business value: Improve customer facing insights and provide internal cross-sell opportunities.

– Develop customer facing, automated cashflow forecasting solution of business account balance data
– Backtest traditional and modern time series methods, to identify best performing models
– Deploy to production

– Solution implemented in Daily IQ application with over 50% of account forecasts producing a 7 day Mean Absolute Percentage Error, of less the 0.2%.
– Product manager received a CEO award.

Text Analytics

Data Science POC

Use Case: Text Analytics of Jetstar customer web chats

Customer: Stellar, Sydney

Business value: Categorising and quantifying customer issues can significantly improve customer satisfaction and loyalty.

– Data profiling of web chat data
– Descriptive analytics, including chat duration, word/term frequencies and automated categorisation
– Sentiment analysis

Outcome: Delivered insights into the quantity and types of issues, degree of resolution and resulting sentiment.

Data Science Project, Predictive Maintenance

Data Science Project

Use Case: Predictive Maintenance of Relief Valves

Customer: Woodside Energy, Perth

Business value: Revise maintenance schedule to minimise downtime and reduce failures.

– Data profiling and data preparation to support survival analysis
– Developed model to describe the lifetime of a relief valve, accounting for Manufacturer and Construction Type

Outcome: Delivered automated solution that groups similar Manufacturers and Types of relief valves, enabling customisation of maintenance schedules and a reduction in failures.

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