Congratulations! The fact that you’re here means you’re probably trying to figure out what career path is right for you. Maybe you are about to graduate or maybe you’re contemplating a career change. Either way, this is an exciting journey, so hang on tight!
In recent years, jobs in data science have become increasingly popular. We have more data than we know what to do with and problems we want to solve. Whether in business, healthcare, space exploration, or another industry, there are endless opportunities to harness the power of data! Successful data scientists use data to tell a story that captivates their audience.
“If data is ‘the new oil’, then the data scientist functions much like an oil refinery, converting data into insights that can both save money and generate capital.” — Eva Short
A data scientist is someone who uses computer programming, statistics, and mathematics to derive meaningful insights from large quantities of data. For example, a data scientist might conduct a cluster analysis of customer characteristics to inform a marketing campaign or build a machine learning model to diagnose cancer.
Data science is a lucrative career path. The May 2018 edition of the BurtchWorks Data Science Salary Survey reported the following salary figures:
|Title||25th Percentile||50th Percentile||75th Percentile||N|
|Entry-Level Data Scientist||$80K||$95K||$110K||97|
|Mid-Level Data Scientist||$114K||$128K||$144K||107|
|Senior Data Scientist||$150K||$165K||$194K||47|
If you answered yes to these questions, it means being a data scientist could be a good fit for you!
There are multiple ways to learn data science, so you can pick the option that works best for you. Here are some examples of learning paths you can take, complete with a discussion of the pros and cons of each approach.
Once you have graduated from a program - be it an MOOC, a graduate degree, or a bootcamp data science program - it will be time to start looking for a job. The best way to prepare for data science interviews is to work on personal projects. There are tons of free datasets available online, so pick a topic that is interesting to you, find a dataset, and start applying your skills. This will help you practice your coding ability while strengthening your resume/portfolio.
As you can see, there are many ways to start your career in data science. But making the career choice that is right for you is important. The bootcamp really helped me to learn a lot from statistics to computer programming in a short period of three to four months. What matters at the end is that you create a plan that best fits YOU and follow it through until the end. Good luck!
This article is contributed by Rifat Yuce Dincer, a graduate of the 16th cohort at NYC Data Science Academy. He spent the first 9 years of his career in business development partnering with c-suite executives solving their business problems with technology, and now he’s a certified data scientist who’s an expert on python, machine learning and visualization.
NYC Data Science Academy offers in-person, live online, and remote self-paced bootcamps. Apply to the next bootcamp early to reserve your seat. The next in-person bootcamp starts on September 23, 2019. Visit NYC Data Science Academy’s blog to review student projects and get updates.
|Courses:||Data Science with Tableau, Deep Learning... View All 9 Courses|
|Subjects:||Data Science, R, Python, Hadoop, Spark|
NYC Data Science Academy offers data science boot camps in full- or part-time formats year-round. Students can attend their programs on campus or online. They also provide a quarterly career day where hiring partners meet students for possible job opportunities.