Dr. Michael Barrowman, PhD

Dr. Michael Barrowman, PhD

Compliance Manager

The Very Group


Dr. Michael Barrowman is a Data Scientist providing independent statistical analysis, currently employed as a Compliance Manager within The Very Group. With a background in both the public and private sector and a wealth of experience working with medical, education and financial datasets. He has produced stunning visualisations for previous clients as well as publication-ready reports and production-ready scripts. He maintains several publicly available software packages for data analysis as well as internal client-based ones.

He has recently completed his doctoral Thesis on Multi-State Clinical Prediction Models in Renal Replacement Therapy, earning him a PhD from the University of Manchester. His PhD project encompasses the development and validation of a multi-state clinical predication model, as well as the methodological advancements to produce such a model. This has led to multiple publications and the creation of software as a by-product.

He is interested in Data Science, particularly using R and python to their fullest potential, encouraging others to do the same and is an advocate for neat and reproducible coding practices. He enjoys web development and learning about web paradigms as wel as learning new programming languages such as C++ and Javascript.

He lives in Merseyside, UK with his partner, two children and two step-children. He enjoys walks down by the local canal, through nearby forested areas and trips to the park as often as possible as his daughter’s favourite outdoor activity is “going on adventures”.


  • HIPAA Privacy Rules
  • Data Science
  • Financial Risk Modelling
  • Clinical Prediction Modelling
  • Multi-State Models


  • PhD in Medicine, 2022

    University of Manchester

  • MSci in Mathematics, 2013

    University of Lancaster








Data Visualisation



Power BI




Compliance Manager

The Very Group

Feb 2022 – Present Speke, Merseyside, UK
Analysing financial data and customer records from a second line defense perspective to ensure the company is compliant to legally binding regulations and internal policies.

Lead Analyst


Dec 2021 – Present Newton-Le-Willows, UK
Providing freelance statistical analysis, reporting and investigations into a wide variety of data problems. This includes Machine-Learning, business intelligence forecasting and Shiny application development.

PhD Candidate

University of Manchester

Oct 2016 – Apr 2022 Manchester, UK
The goal of this PhD is to improve the academic knowledge surrounding Multi-State Clinical Prediction Models (MSCPMs). To accomplish this, I am writing articles to solve methodological issues that are yet to be addressed and applying these novel techniques (along with the present literature) to develop and validate an MSCPM to predict outcomes for Chronic Kidney Disease patients.
(2020). Toward a Framework for the Design, Implementation, and Reporting of Methodology Scoping Reviews. J CLIN EPIDEMIOL.


(2018). Study Investigating the Generalisability of a COPD Trial Based in Primary Care (Salford Lung Study) and the Presence of a Hawthorne Effect. BMJ Open Respir Res.