About Me

I combine data science and market research principles to help companies better understand their customer. Companies that have a thorough understanding of their ideal customer ultimately see better ROI from their marketing initiatives and can further strengthen the market need for their goods and services.

As both a data science consultant and financial writer, I have implemented data solutions in Python and R to help companies solve a range of business issues. This has included building statistical models to allow a marketing company to identify optimal levels of ad spend while maximising revenue, as well as creating reactive, web-based visualization dashboards to analyse pricing and occupancy data of a major hotel chain to better understand customer pricing dynamics and infer future growth patterns.

With a background in economics and statistics, I have devised numerous training courses in Python and R for major educational outlets, including O’Reilly Media and Manning Publications. I have also delivered various training seminars at major data conferences, including Big Data Europe and ML Conference Munich.

Are you interested in learning more about the power of Python and R in the market research space?

Book a free 30 minute consultation with me on Calendly.

Teaching Experience

Time Series Forecasting with Bayesian Modeling. LiveProject series produced for Manning Publications

  • Devised Python-based liveProject series to illustrate modelling of time series shocks with Bayesian Dynamic Linear Modeling, modeling of posterior distributions with PyMC3, MCMC sampling with Prophet, and Structural Time Series Modeling with TensorFlow Probability.

TensorFlow 2.0 Essentials: What’s New. Video seminar produced for O’Reilly Media.

  • Conducted live training of TensorFlow 2.0 using Python - illustrated to students the use of eager execution and AutoGraph, as well as tf.keras for neural network modelling across classification, regression, and time series datasets.

Business Analytics with R: Statistics and Machine Learning. Video series produced for O’Reilly Media.

  • Created extensive video series in the instruction of R illustrating data manipulation techniques, regression analysis and hypothesis testing, along with classification and regression-based machine learning techniques.

Technical Skills

Cloud: AWS, Azure, Render

Languages: Python, R, SQL

Libraries: InterpretML, PyMC3, scikit-learn, statsmodels, TensorFlow

Platforms and relevant tools: PyCharm, Jupyter Notebook, pgAdmin4, RStudio, Git, Docker, Linux

Visualization libraries: Dash, geopandas, ggplot2, matplotlib, plotly, pyplot, seaborn, Shiny