A good number of young students are currently more inclined to tech careers as they hold a great prospect. What these young students and workers need is the right path for reaching their goals and Springboard aims to provide them just that without any unnecessary hustle. The company specializes in the provision of perfect mentorship. Kelvin Tse is the Director and General Manager of Springboard.
Analytics Insight has engaged with him in an exclusive interview to discuss how he manages his role and what he is expecting in the future for the company.
Kindly brief us about the company, its specialization, and the services that your company offers.
Springboard is an online learning platform offering programs in the most in-demand tech careers, including data science, data analytics, machine learning engineering, UI/UX design, software engineering, and cybersecurity. I manage Springboard’s School of Data which includes our data science, data analytics, machine learning engineering, and data engineering programs.
Our big differentiators from other boot camps are that we’re self-paced and mentor-led. Mentorship is really important because we’ve found that students who have a mentor are more likely to finish their program when they have access to someone who can offer real in-the-field advice and act as an accountability partner. The self-paced aspect ensures anyone can enroll, whether you are in mid-career and looking to reskill or brush up on existing skills, a stay-at-home parent with an eye on entering the workforce, or just started your career and want to continue to learn and grow on nights and weekends.
Tell us how your company is contributing to the IoT/AI/big data analytics/robotics/self-driving vehicles/cloud computing industry of the nation and how the company is benefiting the clients.
We’re contributing to every cutting-edge tech industry by training deeply qualified talent. In most tech fields, talent is the limiting factor. Not chip shortages or raw materials, but talent. Data experts are in particularly high demand as of late. Whether hedge funds are predicting the price of a cryptocurrency or a bike share is figuring out how to distribute their bikes across town, data experts are the people turning interesting ideas into efficient, scalable businesses.
Earlier this year, Springboard also joined the Microsoft Accelerate program as a US national partner as a way to bridge that skill gap. We’re focused on tackling unemployment and the digital skills divide by providing technology skills development opportunities for underserved communities. The program is available to residents in Atlanta, Houston, New York, Chicago, and most recently, Miami-Dade.
How is IoT/big data/AI/robotics evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe?
The biggest trend in data science right now is the rise of data engineering. Data engineers are the workers who organize and move the vast amount of data that businesses collect so that data analysts and data scientists can work with it. As data science teams have grown and become more sophisticated, teams are often bottlenecked because of their data engineering capabilities. Per the 2020 Dice Tech Job Report, data engineer postings grew by 50% year-over-year. Since it’s a role that touches everything in tech—AI, machine learning, and data science—it’s going to remain a high-wage, high-demand job.
Do you also feel that the right kind of talent is a challenge in the industry?
It’s the biggest challenge in the industry. The average starting salary for students graduating from our data science course is US$89,000, and many of our students are hired before even graduating from the course. That’s in part due to the breadth and depth of knowledge data workers need to have, particularly in programming and new tools and technologies.
That being said, the data field is one of the most welcoming for people to enter, even later in their careers. Data scientists have some of the most diverse educational backgrounds in tech, and that’s evidence of how valuable data scientists and other data experts are for companies right now—it’s less about the background than ever before. Hiring managers want to know, “Can you perform these duties from day one?” They’re less concerned with when or where you learned those skills.
What are the skill sets that you specifically look for while hiring them at an initial stage?
For students coming out of our data science or data analytics programs, the most in-demand skills are programming, data visualization, and communication skills. Depending on the specific role, business strategy skills can play a big role, too. The most valuable data experts don’t just know how to handle and organize data, but they know how to interpret it and make specific recommendations that affect the product and the bottom line. It’s great to recognize that the bikes for your bike-share company often end up clumped in the same few areas—it’s even better to make a data-supported suggestion on how to ensure bikes are always in the range of interested customers.
What would you advise aspiring big data and analytics candidates?
First of all, it’s my advice to make sure to brush up on your math skills. Math and a programming language will be the foundation of your career. I’d also suggest looking into some of the myriad’s job openings and identifying strengths and weaknesses. What about the job sounds really exciting? What’s less than thrilling? Where are you already ahead of the curve? What requirements would push you out of your comfort zone? That activity will help you identify what skills you need to add to land the job you really want.
Can you throw light on the latest employment trends in the big data and analytics industry?
It’s a great time to be a worker with data and analytics skills. LinkedIn’s 2021 jobs on the rise report found that data scientist and data engineer roles are growing annually by about 35%. Something to keep an eye on is how those roles begin to blend with other tech disciplines. Another tech field with huge demand for skilled workers, cybersecurity, would really benefit from data experts with a cybersecurity specialization. There’s no such thing anymore as a big business without big data, so I doubt that there’s a more future-proof skillset.
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