As an older career changer looking for new challenges, data analytics may appear to be a daunting option. Perhaps you are concerned about starting from scratch, or whether your skill level is appropriate for a new career in data analytics. Furthermore, isn't technology primarily the domain of young people? Wrong.
This takes us back to our titular question: are you too old to start a new career in data analytics? The short answer, in our opinion, is no. We’ll temper this by saying that there are challenges you may need to overcome, though. In this post, we’ll look at exactly what it means to be an older person breaking into data analytics, identifying the benefits and challenges of being “older” in the sector, and some steps you can take to get ahead.
The benefits of being an “older” data analyst
First up, a bit of a confidence boost! What are the tangible benefits of being an older person in data analytics? By “older” here, we’re referring to people aged 30+. That’s not to suggest that being over 30 makes you old. But as we’ve established, within tech, ageism is a problem, so we’ll play along for now and use a deliberately broad definition. To put it another way, as someone with more work and life experience, what are the benefits of being older in data analytics?
You have years of experience Despite common misconceptions, not all companies want 22-year-old data analysts with degrees from Harvard! Older applicants often bring far richer life and business experience. And this depth of knowledge can put you ahead of the younger competition. Whatever industry insights and professional networks you’ve built over the years will be incomparable to those of the average graduate. While you may not begin with the same technical skills as a young data graduate, hiring companies are increasingly alert to the fact that experience can offer more value than a technical qualification alone. You have staying power According to a study by the Korn Ferry Institute, the cost of replacing young talent at Fortune 500 companies ranges from 50-75% of the position’s annual salary. As an older data analyst, you’ll be seen as more reliable than younger hires. Whether you’re planning to stick to a role for the foreseeable future or not, the reality is that younger people tend to job-hop more often than older people. The perception that you’re likely to stick to the job—whether that’s true or not—can work in your favor during the hiring process. You have better writing, communication, and leadership skills Technical skills, like programming knowledge or math, are vital for data analysts. However, the most underrated data analytics skills are ‘soft’ skills (‘power skills’ may be a better name). Carrying out the technical aspects of the role is important but means little if you can’t effectively communicate your findings. From cover letters and applications to presentations and emails, older data analysts (and older workers, generally) tend to have much better writing, communication, and leadership skills, fine-tuned after years of experience. These are the power skills you can only develop over time and set your application apart from the rest of the pile. Plus, your ability to integrate these skills directly into any hybrid role makes you a greater asset.
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