Learning new things is key for your data science career
You’ve made it!
The years of hard work and gaining experience in your field has finally paid off. You’re a Data Scientist! You’re a part of an innovative, forward-thinking team working on exciting, world-changing projects. You’ve got a great salary and tasty benefits package, flexible working and not an uncomfortable suit and tie in sight. Time to put down the books and enjoy the ride? Absolutely not! Quite the opposite in fact, and here is why.
The field of data science is a vast landscape where the possibilities for professionals are endless
It is by no means a static profession – you can apply your skills to an array of industries. Knowledge is key to derive the most valuable insights out of your data. With so many businesses hiring data science teams, it’s important that you have knowledge of the business you’re working in. If you’re looking to move jobs – do your research on the one you’re wanting to make a move into. The job role is so much more than numbers and big data sets. It’s also about contributing to the bigger picture and solving problems for businesses and individuals alike.
Continuing your education in Data Science and all related facets within the field throughout your career will benefit your working life greatly. This real-world application of your work requires constantly learning new skills, technologies, and approaches. You may have done your best work to date, but don’t think that it will be long until someone else discovers a new technique or upgrades a previous methodology.
Stay on top of tools and methods to help you do your job
Frameworks like Hadoop, Spark, or Flink, for example, get regular updates. It’s key that as a Data Scientist, you keep on top of these and continue learning, especially if you’re leading a team of junior Data Scientists.
Contributing to the wider data science community will also stand you in good stead as you actively learn whilst engaging with others. Kaggle competitions are a great way to do this. You can learn collectively whilst having the opportunity to win prize money or secure interviews for some top tech companies. As its typically done outside of work, it shows commitment to your profession, and your ranking will exhibit your capabilities.
Another way to take part in online communities is to start (or contribute) to an open-source project on platforms like GitHub. Here you can code, manage different projects and build and contribute to building software.
Other learning methods
You can often find absolute gems and the latest information by being part of social media communities. Follow relevant blogs, social media accounts, groups, and influencers, and they’re bound to have the latest news on their channels. Don’t just keep it digital – there are a plethora of books being published regularly on the latest tech. KDnuggets recently shared a fantastic resource on 10 free must-reads for Machine Learning and Data Science.
Keeping up to date with the latest research published at top conferences is another great way to stay knowledgeable. Even finding real applications for your own work and business to achieve the best results. If reading isn’t your learning style, YouTube and Ted are goldmines for videos of insightful talks, conferences, and guides that you may find useful. We’ve even compiled a few talks on Robotics, AI and job hunting before!
Learning every day will also help you stay relevant in a competitive job market. Being able to showcase a broad range of skills, and the ability to apply the latest techniques and algorithms to your work will add great value to your resume. Hiring managers for Data Science teams need to know what you can bring to the table, including your passion for the role, which is inextricably linked to self-learning and being an active contributor to the field.
