Analytics Director & Data Scientist | London, UK
A demo customer segmentation dashboard leveraging Python, Scikit-Learn & Plotly to visualise CLV, perform RFM clustering and forecast revenue, turning customer value signals into prioritised retention and growth decisions.
Interactive dashboard built in Plotly-Dash using a probabilistic Bayesian framework to estimate paid media incrementality and ROI, helping compare channel lift and optimise marketing budget allocation.
Interactive dashboard for comparing matched-control, Bayesian inference and other causal methods side-by-side, with rich visuals and uncertainty estimates that support lift validation and experiment readouts.
Hi! I'm Jordan, a London-based Associate Director in Data Science & Analytics, with a focus on what data truly means for business leaders in easy-to-understand terms so they can make better, data-informed decisions. I'm experienced in Bayesian methods, causal inference, experimentation, machine learning and modelling, and working alongside finance, legal, marketing and product teams. With over 12 years of experience, I've managed teams in the Media, Music and Advertising industries, and won an award in 2019 for my work mentoring Data Science apprentices.
.svg){kind=small}
