4 Common Career Paths for Data Science Bootcamp GraduatesBy: Megan Ayraud, Head of Careers at Metis
The data science field is broad, so those who have the necessary mix of skills can venture down a number of exciting, challenging career paths. At Metis, we've had the privilege of training and offering career services to 356 bootcamp graduates (and counting!) across 4 locations. They're now data professionals in industries like finance, e-commerce, education, non-profit, healthcare, sports, and adtech, to name a few, and they boast a range of impressive job titles.
Based on our experience, we've created the following list of common careers for data science bootcamp graduates. We've seen variation in regards to how employers define these different data roles, and oftentimes responsibilities and expectations can overlap. Regardless, read on to better understand the various ways bootcamp graduates can succeed in the still-booming field of data science.
1. Data Scientist
This one is first on our list for obvious reasons. For a second consecutive year, the role of data scientist was named the top job in the U.S. by Glassdoor based on criteria like job satisfaction, median salary, and number of available job openings.
A large percentage of our grads get (and want) this title, because they desire to do what data scientists do: ask and answer the big questions. They want to participate in the entire cycle of data-related problems and solutions, which means their knowledge base has to be substantial and expansive. Data scientists help identify opportunities for companies to use data, while also finding, collecting, and integrating relevant data sources. They do all this while performing analyses of varying degrees of complexity, writing code, and creating tools that teams and businesses can use over time. Additionally, they need to have data visualization skills in order to communicate about all projects, and will need strong verbal communication skills in tandem in order to share findings and ideas with company stakeholders (many of whom may not fully understand technical jargon).
2. Data Analyst
This one's all in the name. The data analyst must possess an astute analytical mind, focusing on creating and communicating insights from data to measure outcomes, make predictions, and guide business decisions. There is often a lighter coding burden placed upon someone with this title (vs. a data scientist), though they may be expected to know certain languages or packages in R or Python. It's also very likely that data analysts will be required to have some set of data visualization skills. When asked to present analysis to interested parties, data visualizations undoubtedly help to get the message across in a clear way. Here too, verbal communication skills are very important, because visualizations can't do all the "talking."
Read about Kimberley Mitchell, a Metis grad who transitioned to a new career in her 50s; she's now a Data Analyst at Newsela.
3. Data Engineer
To be an engineer of any sort, you have to be able to design and build – and when it comes to data, that's no different. A data engineer is a designer, builder, and manager of the information infrastructure for their company or organization. Each engineer develops the architecture that helps analyze and process data, making sure those systems are performing property. Data engineers truly make the jobs of data scientists and data analysts easier, by building systems that make their tasks more efficient.
Read about Metis grad Max Farago, now a Data Engineer at PreciseTarget, where he works with raw retail data.
4. Using Data Science Skills in Non-Traditional Ways
Not all of our graduates desire to become one of the above. Some, instead, want the skills required of those roles in order to use them along other career paths. Take, for example, recent graduate Sameh Saleh, who is currently a Resident Physician of Internal Medicine at UT Southwestern Medical Center. He enrolled in the bootcamp as part of his fourth year of medical school, during which he was allowed up to 12 weeks of independent research.
Why go that route? As he put it in a recent interview: "Large amounts of patient data enable improvement of diagnostic accuracy and efficiency and focus evaluation and treatment of individual patients rather than the incomplete 'one size fits all' model … We are here as health professionals to deliver high-quality, safe, satisfying care at the lowest possible cost. How then can we achieve that mission without this new paradigm shift into the data era? And how can this paradigm shift happen with clinicians on the outside looking in?"
Now he's on the inside, doing his part to help the field of healthcare transition to an even more efficient era, in which physicians will need to understand (at least) the basics of data science in order to effectively communicate with data professionals about what tools they need and how to work with them. Whether in healthcare or another area, data science skills can used broadly and can create opportunity.
Read more about Sameh's career journey.
For anyone interested in honing their data science skills (and who perhaps can't commit to a full-time bootcamp right now), Metis is now offering their part-time Intro to Data Science course in a Live Online format, accessible from anywhere. Learn more about the course and sign up to attend a free sample class here.