Data Science

Data and statistical analysis, econometrics, forecasting, and data visualisation

Practical data science for insight

Modern data science offers powerful tools for working with data, but these methods are most effective when used by someone with practical experience and domain knowledge. Aaron Schiff is highly experienced at applying data analysis methods to understand complex issues and solve real-world problems. He is an expert R user and regularly works with diverse datasets large and small. Aaron’s approach to all data analysis work involves gaining a deep understanding of the data and how it was collected, to analyse it effectively.

Data science services

  • Predictive modelling
  • Causal inference
  • Geospatial analysis and visualisation
  • Development of automated data analysis and reporting pipelines
  • Forecasting
  • Data cleaning and wrangling
  • Development of bespoke statistical and machine learning models
  • Automated text analysis (natural language processing)
  • Static and interactive data visualisation
  • Development of custom R packages

Examples of data science work

Pricing data analysis: Analysis of a large dataset of supermarket pricing and sales, to help the NZ Commerce Commission with its groceries market study by testing for certain features of pricing behaviour by grocery retailers.

Transport forecasting: Developing a bespoke model to help the NZ Ministry of Transport forecast government revenues from fuel excise duties and road user charges.

Aviation forecasting: Statistical models to forecast passenger and aircraft movements for major airports in Australia.

Retail market data analysis: Analysing patterns in a large dataset of consumer usage and expenditure on mobile phone services, to support a review by the NZ Commerce Commission of pricing practices.