So, you think you can be a data scientist. But, are you sure you have it what it takes to excel in the data science field? It's a very complicated field, and getting competitive day by day. In this post, we will go through what the industry demands of a modern data scientist in the real world, how to become a data scientist, top platforms and resources to learn the data science skills, and career advice & job search tips from data science experts. The data scientist job is definitely one of the most lucrative and hyped job roles out there. More and more businesses are becoming data-driven, the world is increasingly becoming more connected and looks like every business will need a data science practice. So, the demand for data scientists is huge. Even better, everyone acknowledges the shortfall of talent in the industry. But, becoming a data scientist is extremely complicated and competitive. The career path of a data scientist is not going to be easy.
It's not hard to find a good story in the tech industry. The problem is that due to the industry's staggering gender gap, most of these stories center on the struggles and accomplishments of men. In this article, we aim to provide a platform for female technologists to share the stories of how they got into engineering, the biggest challenges they've faced, and their advice to the next generation of women in tech. You'll meet a former geologist turned product manager, an academic who fell in love with data science, a senior tech leader who discovered her dream job after the first two companies she worked for folded, and more. CCC's technology solutions are designed to increase connectedness among companies in the automotive industry, including insurance carriers, manufacturers, parts suppliers and collision repair shops. Ranjini Vaidyanathan was in academia and earned a PhD before realizing she had a passion for data science. While changing focuses wasn't always easy, Vaidyanathan said the transition was made easier by some simple, yet powerful, advice from her mentors. "When the going gets tough, what'll help you pull through is your passion for the technical work." How did you get into engineering? I studied applied science and mathematics before finally switching to data science after my PhD. It took me some time to decide what, exactly, I wanted to pursue. I had been doing pen-and-paper theory work as a student, but after a certain point, I realized I found applied problems more interesting. What's the biggest challenge you've faced in your career, and how have you worked to overcome it? Switching fields from academia to data science was challenging. I had to brush up industry-relevant skills like programming, and also adjust to the paradigm shift in thinking, both in terms of technical and soft skills.
Machine learning is one of the most popular topics today. It is also not beginner-friendly, rather the opposite. It is one of those subjects that are hard to start with. This article will give you a roadmap that will help you start with machine learning the easy way. Use the following steps and start learning machine learning today. This may sound as a weird advice since machine learning is based on mathematics and statistics. However, it is the mathematical and statistical side of machine learning that is often the hardest for beginners to swallow. It is not so hard to imagine a guy or girl interested in machine learning. With the current traction of this subject this group is gaining new members every day.
Microbiology and MBA grad JK started to learn about big data and machine learning in his job, but wanted to learn more about data science in a structured environment. He enrolled in Springboard's Machine Learning Career Track to learn about ML and AI online. JK tells us how he balanced his full-time job with the Springboard bootcamp (hint: he didn't sleep much), and how networking at conferences helped him land his new job as a Data Engineer at KPMG! What is your educational and career background? I didn't come from a computer science (CS) background. My undergrad was in microbiology, immunology and molecular genetics. I then completed an MBA with a concentration in Accounting and Finance, working at the Australian Chamber of Commerce in Korea. And that's where I got a taste of some CS database work.
To be honest with you, getting your first job is never easy. It is, in fact, one of the hardest things in your life and you need to put your best effort to find a job in your dream company. The single most important reason for failing those coding job interviews is the lack of knowledge and practice. If you don't don't know much about what to learn then you are bound to fail, hence it becomes increasingly important that you prepare hard in advance. Unfortunately, I learned this a little too late, after spoiling my chances at Microsoft and Amazon, but you don't need to.