From Clinical Nurse to Data Analyst Revolutionizing the Healthcare Industry
Mina Yi is currently a data analyst in an analytics group of a healthcare technology company that focuses on reducing costs, optimizing delivery, and improving the quality of healthcare in the United States. The road to this position is interesting, as Yi started her career with bachelor's degrees in Nursing and Psychology from the University of Rochester.
Yi went on to work as a clinical registered bedside nurse, taking care of patients. Yi notes, "while practicing as a clinician, a few projects that I was involved with at the hospital made me realize that I was naturally drawn to the idea of impact that scales and improving things on a system-level. For that, the work of analysis-oriented roles became my next goal."
Yi moved on to becoming a risk analyst at an insurance company, where she used data to model catastrophe risk. While the position gave Yi foundations of applied statistics and data literacy, she wanted to grow her technology stack to make more of an impact on a broader scale.
"Thinking more long-term, I chose an analysis-oriented route for my next steps because, from the way that I saw it, that would best help me scale that raw energy behind my motivations." Yi wanted to learn data science because of the analysis-oriented work that can scale impact, and since she was living in the Greater New York area, she easily found out about NYC Data Science Academy.
Yi ultimately chose to attend a Remote Data Science bootcamp at NYCDSA because of the breadth and depth of the curriculum, part-time and remote options, and far reaching network. Furthermore, Yi mentions an important reason she chose NYCDSA was "the trust that NYC Data Science Academy had built with the community, including reviews as well as being fully regulated by NYS education law."
After graduation, Yi found herself in a better position to job hunt with many opportunities coming her way. "You become a lot more marketable with the targeted training you gain from NYC Data Science Academy. Several opportunities and exploratory conversations, including the one that led to my new position, opened up without my initiation."
Now in her current position, Yi has the opportunity to make an impactful change in the healthcare industry. Using Python, SQL, and Git, Yi seeks to learn and continually evolve in the data science industry, and she notes "for this stage of my career I couldn't be happier."
"The field and its applications are so vast and evolve very quickly. Learning will be lifelong," says Yi. "There is constant opportunity to exercise and grow in algorithmic thinking and problem-solving. Being close to technology makes it more fast-paced."