Profile
Led by a practitioner, not a slide deck.
Quantile Analytics is led by Panagiotis Papoutsis, PhD — a data scientist with a decade in industry across energy, finance and technology, working where research meets production: operational research, R&D, and models that ship and run rather than sit in a report.
He built and now leads a forecasting team dedicated to European power markets, and currently serves as Head of Data Science & AI on a grid-scale battery-storage programme in South-East Europe. Earlier, as lead data scientist at a European fintech, he built behavioural credit-scoring, transaction-intelligence and risk models.
The PhD — in statistics and machine learning, at École Centrale de Nantes and Sorbonne — was built on quantile regression and Bayesian prediction. That is where the practice takes its name, and its habit of never reporting a number without the uncertainty attached.
linkedin.com/in/panayotis-papoutsisHow we work
A forecast that hides its error is not a forecast.
Quantify the uncertainty
Price series are heavy-tailed and regime-switching. We report intervals, check their calibration, and are honest when the distribution is wide.
Backtest the way you trade
Walk-forward, on the information available at decision time — no leakage from revised data, no cherry-picked windows.
Benchmark the boring model
A network that cannot beat a well-tuned baseline is an expensive way to be wrong. Complexity has to earn its place.
Ship it, then hand it over
Documented, tested, in your repository, with your team able to retrain it. The engagement is finished when you no longer need us.