Chris Murphy’s career goal is to be a data scientist for a Fortune 100 company. He hopes to leverage his experience working in China and his current role as a data analyst at UMass Medical School to reach his goal.
Chris’s undergraduate degree was in Business Administration with a concentration in International Business and a minor in Mandarin Chinese. After graduating in 2019, he decided to move to China for work. He landed a job at a Shanghai startup in the e-commerce space, which is a massive industry in China.
Working at the Shanghai e-commerce startup was a terrific experience that opened my eyes up to the potential data could play in business.
The beginning of Chris' DataCamp journey
How DataCamp helped Chris secure a data analyst position
Chris returned to the US in early February 2020 due to Covid-19 and began his journey with DataCamp, dedicating about an hour each day to improving his data skills. He’s an avid learner who uses several online platforms, but he finds that he’s most consistent with DataCamp. He recently accepted a position with UMass Medical School as a data analyst, and he credits DataCamp with helping him secure the role.
As a data analyst at UMass Medical School, I apply the skills I've learned from DataCamp every single day in my work.
Day in the life of a data analyst
Chris’s day-to-day role at UMass Medical School has a large social impact. His data analysis work supports the Massachusetts State Supplemental Program, which provides monthly funds to over 400,000 eligible aged, disabled, and blind recipients. He uncovers trends, predicts future cash allotment, and ensures current clients’ continued eligibility status.
Our work at UMass Medical School directly impacts our clients’ well-being and livelihood.
How Chris used DataCamp to practice his data analysis skills
Courses in SQL, Python and statistics
Of the skills he’s learned on DataCamp, Chris finds the most useful skills to be in SQL Server (recursive queries, stored procedures, relational databases, etc.) and Python foundations, statistics, and packages (pandas, Numpy, Seaborn, Matplotlib, and scikit-learn).
On a daily basis, I utilize case-specific SQL Server join statements to gather specific data from up-to-date state records. I automate daily reports with text parsing functions. I also rely heavily on the ability to clean DataFrames in data manipulation packages such as pandas. I work with a lot of data involving datetimes, so learning how to handle dates in Python has been crucial.
DataCamp helps learners of all backgrounds become fluent in the languages of data. If you’d like to switch into a data career or level up in your current role, Chris recommends starting with one of our skill tracks.
DataCamp’s skill tracks are arranged sequentially so you first learn the basics, then apply your newly acquired skills to more complex problems. They’re a great step-by-step way to learn at your own pace.
Creating a daily habit
If you’re just beginning your journey with DataCamp, Chris says that a little goes a long way. You can make a daily habit of learning or join the #100DaysOfCode challenge to get the motivation to make a transformative change in your career.
Don’t try to do an entire DataCamp course in one sitting. It’s much easier and effective to digest and reinforce your learning over multiple days than to try to learn everything quickly in a short amount of time.
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Looking for a community of data enthusiasts for support in your learning journey? Join the DataCamp Slack Community, tell the world you’re a data enthusiast with a custom LinkedIn cover image, and connect with Chris on LinkedIn.