Significant Career Lesson From A Data Scientist At Cohere Health
To prepare for a data science career, Shailja emphasizes two key areas: practical coding experience, even if "it wasn't always flashy," gained through seeking out opportunities like assisting professors with data analysis; and relevant domain knowledge, citing their background in neuroscience and EMT work as crucial for understanding healthcare data and effectively collaborating with clinicians. This combination of technical skills and domain expertise, Shailja suggests, makes one a more valuable and effective data scientist.
Coding Experience, Domain Knowledge, Data Analysis, Communication Skills, Healthcare
Advizer Information
Name
Job Title
Company
Undergrad
Grad Programs
Majors
Industries
Job Functions
Traits
Shailja Somani
Data Scientist
Cohere Health
Johns Hopkins University, 2020
Currently pursuing my MS in Applied Data Science at the University of San Diego (part-time online while working full-time)
Psychology
Technology
Data and Analytics
Greek Life Member, LGBTQ
Video Highlights
1. Gain practical coding experience through any available avenues, even if the projects aren't highly advanced or glamorous. Seek out opportunities with professors or researchers to work on real-world data analysis projects.
2. Develop domain expertise relevant to your target industry. Shailja's background in neuroscience and EMT work significantly enhanced her ability to understand and interpret healthcare data, making her a more valuable asset in her career.
3. Combine coding skills with domain knowledge to make a stronger impact. Understanding the context of the data allows for more effective analysis, insightful interpretations, and better collaboration with colleagues from other disciplines.
Transcript
What did you do in undergrad to set yourself up for success in your career?
There are two equally important things. First, get experience coding wherever you can. It doesn't have to be the flashiest project or the coolest machine learning model that predicts everything in the world.
It could be as simple as saying, "Hey, I want more experience coding," and approaching someone working at your university, like a professor. You can offer to analyze their data or work for them. I did things like that with professors at Hopkins when I was an undergrad. It wasn't always flashy, but it showed I had coding experience for actual use cases, not just in an academic setting. You build up from there.
Second, domain knowledge is incredibly important. I work in healthcare, and it's easy for me to communicate with doctors, clinicians, or nurses. This is because I used to work as an EMT, I went to Hopkins, and I have an undergraduate degree in Neuroscience.
Because of this background, I can understand healthcare data better than someone with only a computer science degree. This is a bonus on your resume, whether you work in finance, retail, or healthcare.
Having domain knowledge allows you to confidently say, "I understand this data. I know what it looks like, and I can get insights from it." For example, I know certain values might be out of range or that one piece of data might be more important than another. I can perform gut checks when we build analytics or models. If something appears very important, we can talk to doctors about why that factor is significant in the data. Having this information helps you be more successful in the industry and work more effectively with everyone at your company.