Our team is comprised of genuinely gifted minds

Co-Founder

Stephen Hancock

Stephen is one of Kontexia's co-founders with a passion for machine learning and a drive to constantly learn how to improve techniques to make data easier to understand.

Stephen comes from a background heavy in providing explainable machine learning techniques to financial services, creating solutions that allows them to get maximum value out of their data.

His experience includes:

27+ years experience in quantitative research & trading roles within front office of tier 1 investment banks

17+ years experience in the application of data mining and machine learning techniques to solve problems such as: recommendation systems, prediction of client interests, clustering of client behaviour for segmentation.

Research and development of incremental and explainable machine learning techniques within financial services including: clustering, anomaly detection, n-step prediction and diagnosis.

Co-Founder

Bruno Fontenla

Bruno one of Kontexia's co-founders strives to improve how businesses are able to get the most out of their data. His aim to make data accessible to everyone and for all users to gain maximum value when driving their business endeavours

Bruno, a Kontexia co-founder is constantly striving to improve how businesses are able to get the most value out of their data. His background within financial services, using data on a daily basis to drive his business, means he has seen first hand how the quality of data, and its analysis is vital in everyday working life.

Bruno has:

15+ years experience of quantitative trading and structuring roles within front office of tier 1 investment banks and financial services.

10+ years of applying data mining and machine learning techniques to solves problems such as: credit scoring, portfolio construction and optimisation, market regime classification, systematic structured index optimisation and cross asset propriety risk allocation strategies.

He also has experience in algorithmic trading, audit/due diligence and fraud detection in commodity transaction