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Consultant Profile

Barry Quinn

Areas of Consultancy:
Applied operational research
Bayesian methods
Exploratory data analysis
Forecasting
Multivariate analysis
Neural networks and genetic algorithms
Non-parametric statistics
Probability
Reliability
Sampling
Simulation
Statistical computing
Statistical inference
Survival analysis
Time series

Region of consultancy:
Europe

Profile

I am a lecturer in financial technology and data science in the School of management in Queen's University Belfast. I am a passionate applied statistician who encourages active learning using a growth mindset. I teach students using experiential learning to encourage experimentation and produce credible analytics. My goal is to develop students' employability, resilience, confident humility and empirical curiosity. I run the Masters in quantitative finance and teaches graduate-level statistics for time series and a course on financial machine learning entitled algorithmic trading and investment. Finally, I built and maintained a financial technology platform called Q-RaP, a high-performance cloud computing stack for teaching open science analytics, econometrics, AI and machine learning in the Management School. These resources empower students to create digital solutions to complex business problems which are code-interoperable, credible, and reproducible. I research to feed my curiosity and build confident humility, advocating the responsible use of cutting edge statistics. My current research projects focus on statistical learning in finance, responsible AI, risk and financial regulation in banking, and association football. I have collaborated extensively on industry (see my activities page for projects)

Background

I have been working as a research-active lecturer for 10 years. Furthermore, I have 10 years of finance industry experience, including experience as a quantitative currency trader.

Specialisms

Open science analytics, Cloud computing and financial technology, Financial data science, statistical forecasting, machine learning and predictive analytics.

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