Nathan Green

Senior Research Fellow at UCL

London, England, United Kingdom
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Summary

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Senior
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Top School
Nathan Green is a Chartered Statistician and Senior Research Fellow with 12 years' experience translating advanced Bayesian methods into practical health-economics and HTA decision tools. Based at UCL’s Department of Statistical Science and working concurrently with ICON plc, he specialises in network meta-analysis, cost-effectiveness modelling and R package development, bringing rigorous theory to real-world policy and trial problems. His career spans infectious disease modelling, cardiovascular simulation and government-facing hazard assessment, reflecting a rare blend of academic depth (PhD in Mathematics and Statistics) and applied impact across academia and the civil service. Colleagues rely on him for complex probabilistic modelling and reproducible code, and he’s known for turning sophisticated statistical methods into usable analyses that inform health policy.
code13 years of coding experience
job5 years of employment as a software developer
bookDoctor of Philosophy - PhD Mathematics and Statistics, Doctor of Philosophy - PhD Mathematics and Statistics at University of Liverpool
bookMMATHSTAT Masters degree Mathematics and Statistics, MMATHSTAT Masters degree Mathematics and Statistics at Newcastle University
languagesSpanish
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Stackoverflow

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Github Skills (45)

r-package10
bayesian-data-analysis10
hta10
mcmc10
bayesian10
markov-model10
r9
palm9
rstan9
version-control9
decision-tree9
uncertainty8
excel8
meta-analysis8
survival-analysis8

Programming languages (6)

RCSSC++TeXJavaScriptHTML

Github contributions (5)

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Health-Economics-in-R/QALY

Nov 2016 - Oct 2020

:green_heart: :yellow_heart: :heart: An R package to calculate time-dependent person cost and health functions e.g. quality-adjusted life-years with discounting.
Contributions:1 release, 42 commits, 49 pushes in 3 years 11 months
rr-packagehealth-economicscost-effectiveness
Contributions:136 commits, 6 PRs, 81 pushes in 2 years 3 months
latentcost-effectivenesstuberculosisscreening
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