How to transition from Public Health to Data Science
TL;DR: I worked in public health for several years before learning Python, Tableau, and SQL and switching into a data science consulting role. I increased my salary by 45% and now make over $100,000.
While I have many years of public health experience, my time working as a public administrative analyst at UCLA led me to data science. This role required me to work in regulatory compliance and data management for cancer clinical trials. While I delved into the oncology literature at this job, I also stumbled into learning about the role machine learning can play in predicting cancer and public health overall. This role is how I found my way to data science.
At some point, I realized I needed to go back to school for public health and learn more statistical analysis tools. It was hard to decide between an MS and MPH in Epidemiology or Biostatistics. Eventually, I decided to do an MS in Epidemiology. While in my MS program, I kept learning python and took as many epidemiology and biostatistics classes as possible. Eventually, I did an ORISE fellowship in Data Science at the FDA while in my MS program.
Working at the FDA as a fellow while in my master’s program helped me start combining public health and data science. I focused on data wrangling adverse event data using python. I pulled the adverse event data into Tableau to create a dashboard to understand adverse reactions to medications better.
Now, I work as a Data Scientist at Accenture Federal Services, where I work on various healthcare projects and use my public health knowledge everyday. I primarily attribute getting a Data Scientist position to getting an MS in Epidemiology and completing a certificate in Data Science. I completed two independent study projects using epidemiologic methods while in my MS and a capstone using data science in my certificate program.
Here are some of the classes I took in my summer data science program.
1 Foundations of Data Analytics and Data Science
2 Software Engineering for Data
3 Data Sources & Storage
4 Data Ingestion & Wrangling
5 Data Analysis I: Statistics
6 Data Analysis II: Machine Learning
7 Visual Analytics
8 Applied Data Science (capstone project)
I experienced a salary 45% increase in my salary, moving from public health organizations to working as a data scientist focused on healthcare at a management consulting company. I am now making over $100,000 a year. You can learn more about salary ranges here or https://h1bdata.info/. Also, I used 81cents to help me better understand as someone transitioning from public health to data science to see how much my salary should be.
Overall, I suggest public health professionals who want to get into data science should learn python and SQL. Also, I recommend completing a data science project related to their area of public health expertise. For example, if you are a cancer epidemiologist. You can visualize a cancer dataset in Tableau or perform predictive analytics with a dataset using python, or R. Data.gov is a good source for datasets to use for a data science project.
Please follow me here or on Twitter at @ahobby9. I regularly speak about becoming a healthcare data scientist and public health, and I try to share job openings when I hear about them.