Theo Rashid

Current

2024- Applied Scientist, Amazon, Seattle

• Building forecasting models.
• Alien with extraordinary ability (O1) visa.

Experience

2024 Data Scientist, Faculty, London

• Building an API and LLM application which allows Faculty staff to ask questions about previous internal projects.

2023-24 Freelance Data Scientist

• Modelling soil carbon stock using spatial machine learning methods at Loamin.
• Implementing approximate Bayesian inference algorithms, contract with PyMC labs.
• Modelling food insecurity in Seth Flaxman’s group at the University of Oxford in collaboration with the UN World Food Programme.
• Building scalable Bayesian environmental health models in Robbie Parks’ lab at Columbia University.

2022 Applied Scientist, Amazon, Seattle

• Implementing multivariate probabilistic time series models to forecast product demand in the grocery sector.

Summer 2019 Business Analyst, Deecon Consulting, London

Summer 2018 Researcher, Space and Atmospheric Physics Group, Department of Physics, Imperial College London

Education

2019-23 PhD in Epidemiology & Biostatistics, Imperial College London

• Thesis title: Spatiotemporal modelling of all-cause and cause-specific mortality in England
• Supervised by Majid Ezzati, James Bennett and Seth Flaxman, funded by the President’s Scholarship

2015-19 MSci in Physics with Theoretical Physics, Imperial College London

• First Class Honours

Selected Publications

2024 Rashid, T., Bennett, J.E. et al. (2024). Mortality from leading cancers in districts of England from 2002 to 2019: a population-based, spatiotemporal study. The Lancet Oncology, 25, 86-98.

2023 Rashid, T., Bennett, J.E. et al. (2023). Changes in life expectancy and house prices in London from 2002 to 2019: hyper-resolution spatiotemporal analysis of death registration and real estate data. The Lancet Regional Health Europe, 27, 100580.

2022 Semenova, E., Xu, Y., Howes, A.T., Rashid, T. et al. (2022). PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation. Journal of the Royal Society Interface, 19, 20220094.

2021 Rashid, T., Bennett, J.E. et al. (2021). Life expectancy and risk of death in 6791 communities in England from 2002 to 2019: high-resolution spatiotemporal analysis of civil registration data. The Lancet Public Health, 6, e805-e816.

2020 Kontis, V., Bennett, J.E., Rashid, T. et al. (2020). Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries. Nature Medicine, 26, 1919–1928.

Wang, S., Rashid, T. et al. (2020). A shortening of the lifecycle of major tropical cyclones. Geophysical Research Letters, 47, e2020GL088589.

Talks

2024 Improving Grocery Forecasting with a Bayesian Multivariate Structural Time Series Model, Amazon Consumer Science Summit

2022 The changing mortality patterns in 6791 communities in England, 6th Human Mortality Database Symposium, INED

2021 High-resolution spatiotemporal analysis in 6791 English areas reveals declines in life expectancy, European Public Health Conference

Life expectancy inequality in London, Conference of the International Society for Environmental Epidemiology

High resolution analysis reveals widening 30-year life expectancy gap within London, International Conference on Urban Health

Teaching

2023-24 Instructor, Bayesian Modelling for Environmental Health workshop, Columbia University

2021-23 Head Teaching Assistant, Population Health in the Health Data Analytics and Machine Learning MSc, Imperial College London

Teaching Assistant, Advanced Regression in the Epidemiology MSc, Imperial College London

Teaching Assistant, Statistics for Public Health in the MPH, Imperial College London

Skills