Seth Thomas (he/him)
Senior Analyst, Office for National Statistics
Contact: Email: seth.thomas@ons.gov.uk
LinkedIn: https://www.linkedin.com/in/sethct/
Twitter: @Sethalopod
Personal website: www.sethdoes.com
What does your job actually entail?
I work in the Census and Disability Analysis team at the ONS. My work focuses on using administrative health data linked to Census information to fill in data gaps in the wider disability landscape. We answer policy-facing questions regarding the disabled population, such as our covid-19 mortality analysis. Currently, I spend most of my time in RStudio looking to create an updated version of this mortality analysis with greater resolution on disability imputed from administrative health data. In addition, I’m looking AMIRA analysis to hospital admissions data to investigate the impact of the pandemic in causing disability. Outside of the disability data space, I lead a project on covid-19 variants and their impacts on different ethnicities.
When not at work you can be found…
Either at the local CrossFit gym, in an obscure European city running a marathon in an even obscurer fancy dress costume, or with my head buried in my record collection.
Why did you join the DSxHE community?
My career did a 180 after the onset of the pandemic. When covid struck, I was a marine microbial ecologist researching the influence of microbes on the oceanic carbon cycle and wider climate. My family, like many others, was particularly adversely affected by the pandemic so I was eager to move into a career with a more direct and tangible measure of impact. That’s why I joined the ONS, to work on covid and see my research realised as policy. However, spending the best part of 15 years specialising as a marine biologist left me with certain knowledge gaps, especially in the public health sector. I joined DSxHE to widen my exposure to other professionals in the sector, learn from their approaches and understand potential pitfalls of my own.
What should people reach out to you for help on/with?
I would say that my major strengths – other than wildly inelegant code – are in data engineering, data visualisation and genomics. I’ve acquired a lot of knowledge about the scope and confines of current administrative health data sets and public survey data. I will give my best shot at any solving any R coding issues, but code under the age old proverb “Maybe he’s born with it? Maybe it’s a stranger from Stack Overflow.”
What would you like help with from members of the DSxHE community?
Mainly theoretical QA. I have a wide range of knowledge on statistical and machine learning approaches in microbial ecology. Talking through how these may be applied to health data sets is definitely something I’m interested in.
What’s your interest in data science and/or health equity?
My interest in data science really stems from my marine science days. I moved from a being a lab/field based scientist to someone who sits in front of a computer for most of the days. As an undergraduate, I’d have been appalled at myself. But the really interesting stuff wasn’t whales and dolphins, it was the microbial community and their interactions that really shape global processes. Data science and statistics are really the window to understanding those interactions and processes and I quickly fell in love with it. Applying it to the public health space has only deepened that affection. Now, I can use data science to understand processes or events that are influencing and shaping, in many cases with disability, the day-to-day lives of individuals. I take great satisfaction in seeing the outputs of my team’s work being quickly enacted into policy.
What’s a topic in data science/health equity that you know/care a lot about – why is it important/interesting, tell us about it!
As a member of the Census and Disability Analysis team, it would be remiss of me not to say disability. I think disability has several angles that data science can add to. As a theoretical concept it is complex, which has implications for its measurement in data and understanding what is captured. My work so far has been exploring ways to get more granular understanding and applying this to various international definitions of disability. In addition, disability as a real life experience, also shows great disparities in life outcomes between disabled and non-disabled people. Research that adds to our understanding of the experience of disabled people and tries to overcome data gaps, is directly beneficial. By filling data gaps by linking multiple data sets, more outcomes can be measured but also demand different analysis techniques.
What’s a recent article/book/video/blog/event you’ve come across on data science and/or health equity that you found interesting and why?
It’s not recent, but it was foundational in my transition towards a data science career. Everybody Lies by Seth Stephens-Davidowitz. The author analyses masses of google search data to explore of what big data can tell us about everyday life. It offers insight into the human psyche, deep seated bias, questions we’re afraid to ask another person and information that can instigate a cultural revolution. In summary, it’s wild and an essential read.
What’s a skills/expertise you have in data science/health equity – How did you learn/develop it and how might others do so?
Learning to code functionally was key to moving from academia into data science. There are so many resources that offer to teach R or Python in just 2 hours, but in my experience the majority of them are garbage. As are a lot of books that explain the base languages but little about their day to day use. I really believe that the best way to learn a language is by doing. Take a dataset, however small or large, and ask it a question. Then use resources to explicitly answer that question and that question alone. This builds an applicable skillset, rather than a base general one that you aren’t sure how to use.
What is not a big deal to most people but is torture to you?
Polystyrene. Its use, its texture, the awful squeaking noise that it makes. Everything about its existence really. It’s the most secure way in keeping something from me in the world. A safe? Give me enough time and I could learn to crack it. Put something in a polystyrene box and it is dead to me.
What never fails to make you laugh?
The 20th Century Fox theme tune played really badly on a flute. YouTube it, you won’t regret it.
Which words or phrases do you most overuse?
“Spicy” (Ainsley Harriot gif optional but encouraged)
How do you cope with hardship?
Music. I’m an absolute sucker for an artist in pain. However, it has the unfortunate consequence that some of my now favourite songs have a deep association with some of my least favourite memories. See Towing the Line – Ben Howard and Leaving the Table – Leonard Cohen, to name a few.
What quote resonates with you?
“All men are actors, playing their Fathers until they figure out the man they want to be.” – Hugh Laurie.