Guiding Careers in Data Science, AI, and Cybersecurity with Deborah Sgro

In this episode hosted by Melissa Venable, NCDA Director of Professional Development, Deborah Sgro, founder of Beyond the Glass Ceiling, LLC, and the global mentoring director for Women in Big Data, explains the work and interconnectedness of data science, artificial intelligence (AI), and cybersecurity career fields. She emphasizes the importance of understanding the rapidly growing and transforming tech landscape, highlighting market trends, job roles, essential skills, and training paths. Deb also addresses common misconceptions and the need for continuous learning and adaptability in these professions. The discussion underscores the non-technical career opportunities in these fields and provides advice for career counselors and coaches on how to stay current and support their clients effectively.

Deborah Sgro is a certified career professional with a private practice, Beyond The Glass Ceiling, LLC.  She specializes in coaching technology and business professionals at all levels to achieve their envisioned career. As a former senior financial technologist professional, she worked on Wall Street for over 40 years developing technical solutions addressing business objectives for the New York Stock Exchange, American Stock Exchange, and BNY Mellon. Throughout that time, she also groomed emerging talent by establishing and running mentoring programs, providing on-the-job training sessions, and personally coaching to assist people with their career advancement goals. 

Deborah holds a CCSP certification from the National Career Development Association.  She is also a certified project manager and certified Agile Professional from the Project Management Institute. Deborah holds two master's degrees from Stevens Institute of Technology, one in Computer Science and the other in Technology Management. 

She is on the Board of Advisors for Women in Big Data, and is the Global Mentoring Director for that non-profit professional association. Deborah also addresses corporate women resource groups, university audiences, and presents at NCDA conferences on all aspects of career advancement.

For more information: www.linkedin.com/in/deborahsgro

Resources

• World Economic Forum - Future of Jobs Report 2025
• McKinsey and Company - Featured Insights
• Women in Big Data
• Udemy

Transcript

Career Practitioner Conversations

National Career Development Association

Guiding Careers in Data Science, Artificial Intelligence, and Cybersecurity

I'm Melissa Venable in CDA, director of Professional Development, and I'll be hosting this episode with my guest, Deb Scro. Deb is a career coach. Her private practice, which is called Beyond the Glass Ceiling, LLC. There she specializes in working with technology and business professionals. Deb is also the global mentoring director for the Nonprofit Association, women in Big Data, and also a member of NCDs new AI Task Force. And today she and I are gonna be talking about guiding careers in data science. AI and cybersecurity. Deb, thanks so much for all the work that you're doing, and welcome to the NCDA podcast. 

Oh, thank you, Melissa. It's a real privilege and honor to be speaking with you today. Thank you for the invitation. Oh, we're so glad to have you here and let's go ahead and get started with a little bit of background information. 

So for our listeners who may not be so familiar with these fields, can you give us a simple explanation of what AI data science and cybersecurity are? 

Yes. Happy to. Let's start with data science. Since everything is built on existing or generated data. Now data science involves using algorithms, statistical models, computational tools to analyze and interpret large data sets. They sometimes like to talk of this as the fire hose of data because there's so much data that needs to be managed, and it's the data scientists who are experts in this ability to extract data and generate insights. Think of the data as the output of the data scientists job. Then let's go on to artificial intelligence. Now, this is a field of computer science focused on building systems capable of performing tasks such as decision making, problem solving, pattern recognition, just to name a few u data scientists do work in jobs such as machine learning. Neural networks, you might hear terms like that. Natural language processing. Those are the folks that brought us, Siri and Alexa, and deep learning. Now, usable data from the data scientists are the input to the AI careerists and the AI output is more specific, tailored data and data-driven decisions. Then finally we come to the cybersecurity specialists. Now these folks are involved in protecting systems, networks, and the data from digital attacks, threats, damage. Their work involves the use of strategies and technologies and other practices to defend unauthorized access. Data breaches and cyber attacks, they protect the data and the systems that the data resides on. I hope that was helpful, Melissa. I. That is Deb, I really appreciate how you shared how these three fields are somewhat interconnected. They're all working around and with some of the same parts. And it may be obvious to some, but not so obvious to others why is it so important for us to be paying attention to these fields right now? We've been speaking a lot at NCDA about the negative and positive impact of these careers because these careers are experiencing rapid growth as well as disruption. Now many industries are transforming through digital technologies and have been for years, and this creates both. Challenges and opportunities for the workforce. So in ai. Data science, cybersecurity, these are all central to the transformation, and that came up very clearly in the most recent world Economic Forum meeting in Davos last month. That the, that there will be in the upcoming years in intense focus on industry transformation using these types of career professions. 

So there's a lot of demand. For these high level skills and it's these particular careers are excellent ways to future proof one's work. Which industries are really seeing this demand right now? 

I. Historically, the leaders in innovation adopting innovation have always been healthcare, finance, and technology itself, of course. And they're the ones that are seeing substantial demand for professionals in ai, data science, cybersecurity, and a host of other technically related. Career path. So let me give you an example. In healthcare, data science is very critical for, let's say, clinical trials and research. I. Then the AI specialists come along using that information for partic, for predictive analysis. And of course we rely on the cybersecurity specialists to protect patient data. So that's one example how in the healthcare industry, these three fields work together in concert to provide high quality products. That makes a lot of sense is technology is everywhere, right? So it makes sense that it'd be in something like healthcare as well as in a lot of other kinds of industries. So let's move a little bit to market trends. 

So what are some of the things that our listeners, career counselors, coaches, advisors, should be aware of that are shaping the job opportunities in these fields right now? 

Sure. Lemme just talk about some of the reasons or what's causing this push. And it has to do with, again, going back to the volume of data, being able to handle and utilize that and it, it is all in the service of innovation. And competition. Those are the driving forces, companies, industries that cannot keep up with innovating, recreating, and offering in demand services or products. Are in a position to suffer or lose. So that's the, if you might think the big picture motivation, some of the market trends that's coming out of that would be an emphasis on, I. Cloud computing, being able to use software and machinery anywhere on the internet. Remote work is another motivation for why these trends are accelerating and the need for real-time data analysis and decision making is pushing the growth of these emerging technologists tomorrow. Is not soon enough. It has to be now. So these technical roles, the other point I'd like to make is that these technical roles, as they advance, they're, they are becoming more specialized and will increasingly be integrated in more industries. Driving the demand even further for skilled professionals. I guess we can all say that. We see that coming. No, I think you're right. Technology is something that's, again a part of almost all of our jobs in some way or another. And a lot of the roles in the fields that we're talking about in this conversation really bring to mind those technical skills, things like programming. 

And so my question next is. Are there non-technical career opportunities in these fields of ai, data science and cybersecurity that we should as career professionals be aware of? 

That's a great question. Melissa. Thank you for asking it. And we do have, a lot of examples of folks who work in support of the technologists that we just were mentioning a key set of career paths are both product I. Project management. There's a lot of demand for folks who can work within a technically related industry, not needing to be a technologist, but be able to support the work of the technologist that we just spoke about. Product and pro project management are two key ones. Others that I'd like to mention, policy and ethics specialist. Compliance, regulatory and legal folks. Big demand for people to work in support of technology of those technology careers that we were talking about business and strategy analysts. They're the ones that will be using that generated data. Marketing and communication specialists. How to get the word out about the new products, the new innovations, of course, closer to of interest in our community, HR and talent development specialists. I should have mentioned sales and customer support people as well. Those are just a few that come to mind that work in a supporting role for companies that are digitally transforming, innovating, creating, and utilizing AI I related products. Fantastic. There's, there are opportunities everywhere to get involved here. There's opportunities everywhere. Yeah. Oh, and I'd like to say, no doubt there will be more to come. No doubt. No doubt. And I'll just briefly share in preparing for our conversation, I was researching and looking and reading, and I came across for the first time. A career path called AI explainer, and it's a, it is a individual in the technical chain between the engineers and the end users who has the responsibility to. Help those two professions understand each other. So something that was just newly newly created. Since all of this is happening, AI explainers. 

A great example of how AI maybe is eliminating some jobs, but creating brand new ones 

Absolutely. That are out there. Absolutely. Which would be a big plus for people who specialize in either oral written communications interpersonal communications, a huge asset for folks in, in that career path. So let's dig in a little bit more to skills and qualifications for these fields and what would you consider are the essential skills to enter AI data science and cybersecurity jobs? I. Yeah. There's some that overlap all three. And when I speak about them I'll talk about the individual ones for ai, data science and cybersecurity. And you might hear that there are similarities between them and that makes sense. So let's start again with data science. A strong proficiency in statistics. In the ability to utilize data and turn it into visual knowledge, that's a specialty called data visualization. Career coaches might come across job descriptions that talk about data visualization, and that's simply turning numbers into pictures, cloud computing, utilizing resources throughout. The web, the internet programming, you might come across programming languages for the first time, Python R, the letter R or SQL is also known as analytical thinking Data, storytelling and understanding. This is a key one that we don't talk about enough. Understanding industry needs. What is the particular aspect of the industry? One is working in what challenges so that they have, so that the data scientist is knowledgeable in those that understanding to make the data useful for their end users. Now moving on to ai. Strong understanding of cloud computing once again, but uniquely machine learning algorithms, how to train machines to create these systems. Programming languages. Again, Python are analytical and problem solving skills. And I wanna say it again, industry specific knowledge. You need to know the business of the business you are in. Let's look at cybersecurity, a little more specialized here. Knowledge of network security protocols, programming, of course, threat detection, understanding and mastery of cryptography and encryption forensics. Risk assessment, no surprises mentioning this in careers that are looking to defend and protect systems and data, vulnerability management, attention to detail. And the other one that is very important in a cybersecurity world is ethical responsibility to handle sensitive data with integrity. So that's a flavor. Of the technical, the interpersonal, and the business acumen skills that are required for these overlapping career paths. 

Oh, thank you, Deb. Again, there's a wide range of things going on there. And so my next question is related to training. Should someone that's interested in these fields pursue a college degree, an advanced degree certification, go to a bootcamp. What are the recommendations there? 

Yeah. Thank you for this question because in my private coaching practice and and leading a global mentoring initiative, this comes up a lot. People want to know how to create a strategy both to enter these fields and to advance within these fields. So let me just start out with a little introduction. Reminding folks that careers that we're talking about are focused on specialized knowledge and skills. Are built on very advanced concepts requiring a wide variety of expertise, knowledge, skills. You heard from that inventory in the previous question, the breadth. Of knowledge as well as the depth of knowledge that is required to be a strong performer. Now having a formal degree provides solid and most importantly, Melissa Comprehensive Foundation. It gives one that breath, it gives one the ability to develop both critical and analytical thinking. However, formal education may not be available to everyone. And there are other paths to acquire learning experiences through boot camps. Very popular. And there are some very reputable, mostly these are commercial. Offerings. Although a number of professional associations like the one I'm affiliated with women in big data they do have arrangements with commercial providers to offer free licenses, nonprofit associations, working with commercial providers to offer free licenses. To their membership. So there are a variety of ways that someone could avail themselves to boot camps LinkedIn courses. As well as pursuing certifications. The need for continuous learning and upskilling, however you enter the field, is a constant requirement. It's not a one on and done situation. I'd like to also mention that. In the technology fields, there's also other learning opportunities, and these take the shape of datat thoughts, hackathons, coding competitions, creating open source. Code to be evaluated by peer professionals. So there's very creative ways that one could put together, assemble a constant upskilling, continual learning plan using the combination of these. Whether you start with formal education, you're going to need bootcamps and certifications and hackathons. Whether you start with bootcamp, you're going to need to use a variety of educational avenues to keep abreast of the changing technology because, vulnerability and constant change is. Part of the field that, that we work in when we work in technology. 

So what I'm hearing you say is that you're always gonna be learning, and you're gonna have to do that in lots of different ways if you're gonna stay current, which you're gonna have to do to really be successful in these fields.

Exactly. YY yes, because. Let me anecdotally tell you a little bit about my career. I had a 40 year career in financial technology working on Wall Street, and I started at the time when many computers were coming in replacing the mainframes. So in my 40 year career, starting with many computers. And then finding our way to the internet, to cybersecurity, to remote access huge changes in a single lifetime, a single co. Yes, it is one of the requirements is to stay agile and resilient in, in one's learning. 

Thanks for sharing a little bit of your story there, Deb. That's super helpful and interesting as well. You're right, it just, it's moving so quickly that if you're not willing to move with it you're going to definitely limit your opportunities. So can, you can you move into misconceptions about the qualifications that are needed in these fields? What are perhaps some of the myths out there about working in ai, data science and cybersecurity? 

Yeah, some of them. Let's go back to the question you asked me before. I think one of the myths is that the only type of jobs in these fields are technical jobs, traditionally technical jobs, and that's not the case. There are a lot of examples that we just spoke about where other professionals are needed. For a company to achieve its financial and strategic goals. So that's misconception one that they're not all technical jobs. Another misconception I is that people who are entering this field believe that the only coin of currency they need is their technical skills, and that is a. Really big mistake if someone follows that strategy of only developing their technical skills, the two others that are needed, we mentioned them before, interpersonal skills, communication, collaboration, setting expectation, negotiation convincing, motivating, influencing, that's the second set of skills that are required at all levels, not just at the leadership level, at all levels of one's career. And the third set of skills is the business acumen, knowing the business of the business you're in. Being able to make decisions, technical decisions, product decisions by reading financial statements and understanding the role of your company as it comes to regulations, compliance, a competition threats or. Understanding how your company is placed and what you need to do to meet those challenges. So that's the second mis misconception. It's not just technology. You need that combination of technical, interpersonal, and business acumen skills. And then the third, I think it goes back to education. Some folks. Shy away from these fields thinking that they must have advanced degrees like PhDs. Now, many do. Many do, depending on what kind of job they're looking for. Academic research in technology research scientists, AI research scientists, those folks. Yes. PhDs and doctorates are required, but for the most part it is not a an eliminating requirement for other work within ai, data science or cybersecurity. Does that help Melissa? 

It does. It really does. And you've introduced some new things and also confirmed some things I think maybe many of our listeners were already somewhat aware of. And so far we've covered a lot of ground here, Deb, we've talked about market trends, job roles, qualifications and training, and the skills required. So for our career counselors and coaches that are listening in, what do you think are the most common barriers to entry for their students and clients? 

Again, relying both on my professional experience and long career in these fields. These are competitive fields because they are lucrative. So one of the barriers, and this is where I focus a lot of the mentoring and coaching work that I do, one has to be able to advocate for one's career. Thinking your work is going to speak for itself. Those days are over if they ever existed. So the ability to compete. Know your worth and communicate your worth. This is a common barrier that people have for a lot of reasons, personal, social, cultural. There's a lot of reasons why that skill may feel taboo. But it is a barrier that one does have to work beyond. That brings us to the conversation of confidence. Being able to successfully communicate one's interest skills, needs worth value and the idea that. Our education, our learning is not a one and done. We've said it a few times and it bears being repeated because unless someone purposefully engages a curious mindset, a discovery mindset, a innovation mindset, they're at risk of not upskilling. They resist change. There's unwillingness to experiment and explore, and that career goes into a flat lining state just going along doing what one has been doing for whatever timeframe we wanna talk about. Now, a good career coach can assist a person. Who is at risk of flat lining because the next step after flat lining is completely derailing one's career. It's almost as though you are building in your own obsolescence. So the other barrier is to make sure that our clients, our students, understand. That this is a a growth process, not only for those in technology. I would say for any career path that probably is true as well. 

I think you're right there, Deb. And we've gotta worry about our own flat lining, right? As career coaches and counselors, we need to make sure that our knowledge and skills are staying relevant particularly in these fields, ai, data science, cybersecurity, that are, they're not going anywhere and they're evolving very quickly. So what are the key resources that our listeners should be using to stay up to date? 

There are many, but however, let me just start by giving some thoughts on a way to think about this where career coaches, professionals, counselors one thing they might notice within themselves is how comfortable are they? E even listening to new language like Python R penetration testing data engineering how comfortable are we in. Listening to that language or reading that language and finding out a little bit about it, even if you just know the words and are familiar with the words, that is a strong foundation to be working from. Following up on that courses, whether they be industry webinars, following experts on platforms like LinkedIn. Taking short courses in Coursera, Udemi the typical learning platforms, just even exposing oneself to the language, understanding some relationships through whether private study, reading industry publications like Wired, Forbes, Harvard Business Review. Staying current with business trends I am always on McKinsey and Company's website, get their newsletters. I always look for the World Economic Forum to give me insight into. What are the industry leaders thinking? What do they see, the trends? That, that is important insight for me. Melissa if I may, I'd like to make one other point here. We don't have to be experts in every field. I think it's important that we have. At least enough understanding on what the conversations are, what the concepts might be, and figure out a way to connect our clients and students with people who are experts in that field. Just something that I'd like to share. I was a technology project manager. And what that meant is that I was working with large teams of architects, coders, network engineers, et cetera, et cetera, et cetera. There is no way I would have been able to direct all of those experts what I needed to know. Was, what was the main concepts, how to talk to them and how to ask questions intelligently to draw out the risks, the benefits, the pros, the cons. So even when you're in a technology field, you are not the master or expert in every aspect of it. This is great advice. It's just unrealistic to expect that you're going to have. Expertise in all of these areas. And it's okay to not pressure yourself to seek out that expertise and or even to present yourself as an expert to the students and clients that you're working with. But if you know the resources and you've got a network that you can help connect them with. 

And that can be part of the part of the solution there. Deb this has been wonderful. I really, again, appreciate you bringing all of your expertise and this topic to, to NC DA's listeners. So as we wrap up here, if there's one piece of advice that you could give career coaches and counselors about these technical fields, what would it be? 

Yeah, thank you for that question. I would say. Stay focused on the big picture. Don't worry about the small details. Someone else is prepared to worry about the small details. Stay focused on the big picture. Be curious and be adaptable. Allow yourself to. Inquisitive inquisitive enough that when you're reading job descriptions, when you're talking to headhunters, whatever that you don't shut down just because they used a word or talked about a concept that you might not have been for familiar. Feel free to say, tell me more. Tell me why. Those are the tools that I find helpful. When I'm pursuing an area that I may not be comfortable in. 

This is fantastic and your enthusiasm for this subject and your encouragement to all of us that we can get ready to help our students and clients with these fields and the questions that they may have and the barriers they may be trying to overcome. Thanks again for being here and we look forward to hearing more about your work in the future and that of the NCDA task force. 

Oh, thank you, Melissa. It was a great pleasure. I enjoyed speaking with you.