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Consultant Profile

SA

Stephen Azeez

Areas of Consultancy:
Expert systems
Exploratory data analysis
Forecasting
Multivariate analysis
Non-parametric statistics
Numerical analysis and optimisation
Spatial statistics
Statistical computing
Statistical inference
Time series

Region of consultancy:
Worldwide

Profile

Stephen Azeez is a Statistical Consultant specializing in applying advanced statistical methods to solve complex real-world problems across risk modeling, predictive analytics, and decision systems. His expertise includes exploratory data analysis, forecasting, non-parametric statistics, numerical analysis and optimization, expert systems, spatial statistics, statistical computing, and inference. With a focus on bridging quantitative techniques and business strategy, Stephen has delivered impactful solutions in financial services and technology sectors, developing robust models, scalable analytical frameworks, and actionable insights that drive informed decision-making. He also contributes to the field through publications, academic supervision, and peer review in AI and applied statistics.

Background

B.tech Applied Math; MRes Applied Computing: Chartered Statistician (RSS); Chartered Mathematician (IMA); Certified Mgt Consultant (IMC); Fellow, IMC.

Specialisms

Stephen Azeez is a Statistical Consultant specializing in applying advanced statistical methods to solve complex real-world problems across risk modeling, predictive analytics, and decision systems. His expertise includes exploratory data analysis, forecasting, non-parametric statistics, numerical analysis and optimization, expert systems, spatial statistics, statistical computing, and inference. With a focus on bridging quantitative techniques and business strategy, Stephen has delivered impactful solutions in financial services and technology sectors, developing robust models, scalable analytical frameworks, and actionable insights that drive informed decision-making. He also contributes to the field through publications, academic supervision, and peer review in AI and applied statistics.

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