When it comes to new year’s resolutions that involve career moves or goals, it may take months or even years to accomplish such aims. For example, to become a data scientist, you must put in the work, gain experience with your own passion projects, and develop your skills over time to really change your career path.
It can be hard to know where to start and often investing time in the wrong skills can distract you from reaching your end goal. In a recent webinar, Steven Hillion and Catalina Herrera answered questions from the data science community on where to focus your energy and how to get hired as a data scientist in 2021.
How to get started and gain experience?
Oftentimes when you’re coming right out of university, you may feel you have little or no working experience. It’s the classic chicken and the egg problem. I need a job to gain experience, but I don’t have the experience to get the job. In this case, Hillion advises, “Don’t rely on just the classes you’ve taken and the projects you’ve done as a part of those classes.”
Even if you’re unable to get an internship, self-motivated projects using public data are a great way to get your foot in the door and show a natural curiosity by exploring data and answering your own questions. Also, non-profits and small businesses could use volunteers to solve their problems with their data. Herrera cautions however to “ensure whatever you put your energy in that you are passionate about it, have some background in it, and understand the topic.” This helps make the process both fun and fulfilling.
What kinds of hands-on experience do you need?
Ground level, you need some type of statistical and machine learning experience. It’s a very broad field, but there are core techniques and methods that you should be familiar with, including classification, regression, clustering, dimensionality reduction, text analytics, time series, as well as basic statistical and probability functions.
There’s really no shortage of free resources to learn about methods and how to apply your data science knowledge. In fact, at TIBCO we have Doctor Data Science and Doctor Spotfire, which are monthly programs where TIBCO data scientists will take you through a couple of standard techniques. Past sessions are available on Youtube, covering everything from neural networks to time series to categorical encoding.
What technical skills need to be part of your resume?
Python is the obvious thing to mention. R is still current, but Python is the place to start. Although, the most commonly used programming language remains SQL. Nothing new there, but is the language of data and very important to know. It’s fairly straightforward and scalable. For big data, Spark is worth learning as well. And beyond languages, you’ll want at least a college-level class in statistics and online classes on machine learning.
How to find a job?
May feel like you’re throwing your resume into a black hole if you’re just applying to job boards. Leverage your network and find a way to connect to the jobs that appeal to you through your network or through projects that the team may be working on currently. Recruiting fairs and meetups are also helpful in making connections.Even if you’re unable to get an internship, self-motivated projects using public data are a great way to get your foot in the door and show a natural curiosity by exploring data and answering your own questions. Click To Tweet
The process of becoming a data scientist and getting hired can feel overwhelming but remember you’re not alone and we want to help. Make sure to watch the full webinar for more expert advice and insight into the hiring process.