I am a data scientist with a background in quantitative social science and policy research, specialized in Bayesian statistics and various
approaches to causal inference. I currently work as a Senior Data Research Scientist at Covered California, where my research evaluates
Covered California’s efforts to provide quality healthcare and improve health care outcomes for all Californians.
My background is in anthropology. In 2023 I completed my PhD at UCLA, where I led a 6-year collaborative research program using Bayesian multilevel regression modeling, machine learning and various approaches to causal inference to test the efficacy of US public policy solutions to gender-based income inequality. For example, in one study I quantified the gender gap in US parents’ loss of income after having a first child, and tested how state-level family leave policies affect this ‘child penalty’. As an anthropologist I learned to connect quantitative data to real human experiences and develop nuanced data-driven stories that inform policy.
You can download my full resume here.
Social inequality and policy
In the last year of grad school I focused on applying my anthropological background to studying the actual and potential impact of
social policies on people’s lives. For example, in one study I examined the US 'child penalty': the earnings parents - especially
mothers - lose after having a first child. As a research fellow at the WORLD Policy Analysis Center
I evaluated the impact of disability policies on the economic situation of people with disabilities in low- and middle-income countries.
My formal graduate education is in behavioral ecology. This field seeks to use evolutionary theory to explain and predict how
individual-level and population-wide socio-ecological factors have shaped human evolution and shape people’s behavior. My dissertation
research is focused on issues regarding social norms and gender inequality, such as on changing norms regarding maternal health and
infant care among women in rural Namibia, and gender inequality in temporal income dynamics when parents have a first child.
Using the rigorous training in multi-variate regression I received at UCLA, I sought out my own education in Bayesian
statistics for the social sciences. There are so many amazing resources that exist for this online! I learned the basics of
Bayesian inference through Richard McElreath's online course Statistical Rethinking
and further built on this knowledge using online sources such as Bayes Rules! by
Alicia Johnson, Miles Ott and Mine Dogucu, Andrew Heiss' blog, and
Causal Inference: the Mixed tape from Scott Cunningham.
Good visualization of data and statistical results is crucial to clear science communication, and I like to experiment with new ways to
communicate information. Below are a few examples of visualizations I've made for previous projects. I ahve also created interactive dashboards
where users can point-and-click to choose the information and plot types they want to see.
I identify as an R lady! There are just so many things you can do with R: data cleaning, statistics, data visualization... even website building!
Besides my love for R I enjoy working in Python, am very comfortable using SQL for data management, Ubuntu and Unix for working on secure
high performance computing servers, and I've created a few Android apps in Dart. Take a look at my GitHub
to see some examples of projects in R and Python. Lastly, I've also built a few websites with html - such as this one, so you can be the judge
of my skills ;) I enjoy learning new languages and am excited to increase this list!
I will list my publications here later. For now, check them out on Google Scholar!
Cycling is an important part of my life. I was a collegiate rower in the Netherlands, and when I moved to LA this became my main hobby. At this moment I'm captain of Velo Club La Grange's women's road race team. 2024 was also my second year participating in AIDS/LifeCycle, a ride from San Fransisco to Los Angeles to raise funds for HIV/AIDS prevention and treatment in these cities. I've raised a total of almost $10,000 dollars towards this cause, and am signed up again for next year! You can learn more about the ride and sponsor me here.