Cracking the Code: The Untold Impact of Data Science Careers!

Welcome back to the Ally from Corporate Podcast. It's a beautiful day in Las Vegas and today I have a very special guest, one that I have known for every waking minute of my life. Our parents knew each other before we were born. I'm very excited to have her on here. Today we have Maya Wilson, the head of data science for Series C Startup. Hello, Maya.

Hi. Thanks for having me. Allison, be so formal.

Come on, we're friends.

So you say.

I'm so glad you're here today. You have come to Vegas for the HR Tech conference and you brought me along with you one day, which was awesome. And I'd love to talk about the talk we saw yesterday. But first, you have had a very meandering career path and a lot of people listening to this are thinking of switching industries or they're curious about a different industry than they're in. Tell me a little bit about your career path and how you got to where you are today.

Yeah. So I started my career in academia. I'm a political scientist by training. And part of this for me was I graduated with my bachelor's degree in 2010. The recession was starting. It was a really bad time to be entering the job market. I didn't have a lot of marketable skills. I was a really good babysitter and I was a decent research analyst. And I kind of wanted to stall that transition to the real world. So I figured, hey, I'm good at research, might as well go for a PhD. And so I kind of spent the next five and a half years getting my PhD. And early in I realized I really didn't want to go into academia. I didn't enjoy the research aspects of it. I didn't enjoy the kind of ivory tower feeling of it. But I had already moved to Atlanta and I was partway through the program, so I figured I'll go ahead and just finish it. And so when I was partway through the term, data science became part of kind of job culture and big data was becoming a thing. Compute power was becoming powerful enough to really drive a lot of insights with data. And so I started to shift my focus to tech. And during my time in my PhD program, I really invested in coding skills and getting a lot of hands on experience with data. And then when I graduated, I ended up getting a job as a data scientist at a very early stage company. I was employee number 16. It's a SaaS company, so we built software and I had an awesome experience there for about three and a half years. I was a data scientist and kind of practically a software engineer because we were just so small. But I was able to really get hands on there and learn a lot about software engineering. I had some great mentors there, did some product management as well. It's one of the fun things about startups is you really get to wear a lot of hats. So I got to learn a lot of different roles within the company. And after I was kind of ready for something more, some growth. I wanted to become a manager. And there wasn't really a big enough data science team at this company to become a manager. So I got a job at a much larger company as a data science manager. I inherited a team of six data scientists, learned a lot about people management, had the opportunity to grow my team in size, I could hire a bunch of people and we really got to work in kind of the forefront of generative AI. We were building a lot of things that would generate text for our customers even before OpenAI was out there. So that was really fun. And then most recently I left that role to join to go back to a startup. I really enjoy startups. I like wearing a lot of hats. I like getting to kind of expand my role to fill the places that need to be filled. And so I've been at this new company for about two months and I lead the data science team. I get to set data science and AI strategy and it's been really fun so far.

I love that. I love the part where you say you wanted to go back to a startup. I get a lot of questions about startup versus big company life. And the wearing many hats thing is absolutely true. I would say the startup life is not for me at this point in my career. However, I've done big company and I've done startup and I like both for different reasons. And I like the stability and the pace of a larger company. It's a little bit slower and I feel like the dynamic, fast paced environment of a startup is sometimes a little chaotic, but you feel like you're able to be creative in that situation.

I love the chaos because it makes me feel like I'm moving fast. Yeah, I'm really driven to move fast and to fail fast and make mistakes and learn new things. And I felt my time at a big company had a lot of process involved and I understand why that's important. You know, when you have big organizations, everyone needs to be aligned. You need to make sure you're using resources well. But my time being back at a startup is already just my ability to move quickly. I've Been given the advice to ask for forgiveness, not permission. The speed I like to move, and startups are a great fit for that.

And tell me what you mean when you say fail fast, because some people are very scared of making mistakes at work or learning things. Things the hard way. What does failing fast mean?

So I work in product development, and a lot of what we're doing is trying to see whether new solutions will solve a customer's problem. And so a lot of my role is sitting with customers and learning about the challenges that they're facing, the things that our software could help with, and proposing solutions for AI. How can AI help solve this problem? But oftentimes, and especially with AI, the only way you can tell is by trying it. Like, we can paint some abstract picture and like, say, sure, that sounds great, but then you spend six months, months to a year investing in building something that then doesn't solve the customer's problem or wasn't what they needed or it doesn't work. Sometimes it just doesn't work the way that you want it to. And so in my role, I really try to work with prototyping. I try to do kind of a minimal investment and put it in front of a customer. Is this what you're looking for? Are you going to interact with this? Under what conditions would this be valuable or not? And we get so much insight from. From those kind of lightweight prototypes, putting them in front of customers. And so I have a lot of space in my role to build just a very small version of something and try it out. And sometimes that means people get really excited about it. And then we build some investment and we put it on the roadmap and we, like, allocate teams to it and kind of more formally invest in it. And sometimes it means that someone just says, I would never use this. This doesn't solve my problem. I'm not gonna go do that thing.

And you don't get emotional like, oh, I've put so much of my heart and soul into this.

Well, that's why you want to fail fast, right? If I put six months to a year into it, yeah, that's gonna suck.

Yeah, that works.

If I put, you know, three afternoons building a little prototype and show it to a customer on a call and they don't like it, or the product manager says, yeah, we're not gonna invest in this. All right, it was a few afternoons. But that's innovation for you. So that's why I say fail fast instead of failing long. Like, you're gonna have failures if you're not failing. You're not trying enough. You're not being innovative enough. Like, you should have some failures, or you're not, you know, really going to be innovating, but you don't want to invest too much before you fail. And so I think, you know, failing fast from a personal level is a little bit harder. Right. Like, you can't necessarily go out and just experiment with, like, ooh, what if I, you know, talk back to my boss? Let's see how that works.

Don't do that.

That may or may not work. I have had managers that really welcome. My current manager is one of those really welcome direct discussions and, like, you know, challenge me if you think so. And I've had managers that don't want that at all.

Direct discussions freak me out. I like to work for managers that are very complimentary, very soft around the edges. They sugarcoat things. So you like the direct approach?

I do. It stings sometimes. Yeah. I find that I grow more from a direct approach. I really appreciate it when I have a manager that will just tell me, like, hey, don't do it that way, or this thing didn't come off the way you thought it was going to. I would rather that. But it doesn't mean that it doesn't sting when it happens.

Yeah, but then I guess you. It stings for a little bit, but then you grow and you can change direction or slow down or speed up whatever their feedback was. So you say you're a manager, and we're talking about you receiving feedback in a different way than I like to receive back. Receive feedback. What do you think somebody could do if their manager is giving them feedback in a way that they don't like to receive it? Do you think that a conversation can be had and somebody can say, hey, I know you're giving me some feedback right now. I really like this style of communication. Do you think we can adapt? I mean, do you think that's possible?

You know, I think feedback is a gift, and I think if you ask people not to give it to you, you're just gonna stop getting it, like wearing the manager hat. If one of my employees said, hey, I don't like the way that you gave me that feedback. And I've had this happen before. I've had employees that are not receptive to feedback, and. And we kind of stop growing together, and they stop being quite as good a fit on my team. Because for me, as a leader, I want to be able to grow my team to be able to fill the space that we're working towards to be able to be the leaders that I'm looking for from them. And if they're not receptive to my feedback, I don't have the faith that they're going to be able to do that. It's caused problems in the past. Now, can I have someone say, hey, that feels really harsh, or that hurt my feelings the way that you said that. Sure. You can give feedback like that. You can say, like, I don't know if you meant this that. That way, but that made me, you know, I had a really terrible weekend because of the way that you phrased that or something like that. You know, make it about the way that you reacted to it. But you're not going to change your manager. You're not going to say, like, can you, for me, give more of a sandwich kind of feedback with more compliments in it? So. And you want to be careful with that, too. Like, treat feedback as a gift. I have a rule that every time someone gives me feedback, no matter how much it hurts, I say thank you. Thank you for that feedback.

I love that phrase because it just.

It kind of conditions you to, like, retrain your brain. This is a gift. It sucks. And I wish I was perfect, but I'm not. And the way that I'm gonna get better is if I keep encouraging people to give me this feedback. Especially as a manager and as an employee, that manager, employee relationship, you need to have those open channels of communication, because when they're not there, it's hard to figure out how you're gonna continue to grow together.

Yes. And if you're working in a fast pa, like a startup, if you, as the manager sees a change in the wind and you need your team to pivot, you might give feedback to your team or you might brief them on this new direction we're going in, and that might be taken as feedback. And if somebody's not very receptive to that, the train's going to leave without them. And like you said that you're going to grow apart and their efforts are not going to be aligned with their division or their department. So, yeah, I think. I think receiving feedback in a healthy way is a skill in itself. And I don't know where people learn that, but, yeah, it's hard.

It's hard. I had someone tell me once, as a manager, as a leader, you're only as strong as your team. And so if I can't help my team get stronger, like, I don't want them on my team.

Yeah. And I thought I think a lot of managers are more passive than that. They don't care so much. The really good managers that I met, that I have met, they do really care. But I have had some managers that just seem like they don't really care if their team is aligned in the direction their team's going in. They just kind of delegate tasks and there's no real purpose or direction. But I like your, I like your ideology with management.

And ultimately those managers that aren't setting direction and aren't bringing their teams and investing in creating vision and pulling the team towards where they want to go, like, that's not a great team to be on either. I don't want to be on that team. No. So, you know, Rising Tide lifts all boats. Having a strong manager that invests in the team is good for the team. It may sting, but in the long run, you're going to have someone that knows where they want to go, knows how to help the people on the team get there, and that's better for everyone. Yeah.

And I, I don't know if we've ever talked about this. The difference between a boss and a leader. You know, a boss is more like the stick versus the carrot. A leader inspires. But one of the best managers that I ever had used to give me feedback in such a subtle way. He would almost use the Socratic method to ask me questions and he would lead me to say the, the feedback out loud myself. He would ask me questions and we'd have a conversation and then suddenly I'd say, oh, maybe it, maybe I didn't do that the right way. How about I try this next time? And he'd go, yeah, that's a great idea. But he could have just said, I have some feedback for you. You need to do it this way next time. And I would have gone, okay. But it was like he led me to the idea myself. And it was almost like I gave myself the feedback. And I loved that about him.

It also makes the feedback so much more effective. I did the same thing. I start with questions and what I've learned is that there's often context. I wasn't aw that led the person to do it the way that they did it.

You're so self aware.

Sometimes it means that my feedback isn't as relevant as I thought it was going into the conversation. And sometimes it means that I'm better able to tailor the feedback knowing where they were coming from. So I do the same thing. I'll ask like, hey, you know, tell me about this interaction that happened. Or like I'll witness something in some meeting, maybe someone gives a presentation that doesn't land right and I'll say, hey, you know, tell me about where you were coming from with that and I'll learn more about the context and I can say, okay, given what I know here, let's make it shorter. That wasn't the right audience for that. We need a little bit more of a high level approach for that type of presentation because it was too technical for the audience you were going to. But I can see why, based on the person who asked you to give this presentation, you did it the way that you did it or something. So starting with assuming that you as the person giving feedback, don't know everything that you need to know in order to make sure that feedback's relevant. And sometimes if you don't ask those questions, you're going to step in it, you're going to give feedback or, you know, advice or something. It's like not relevant and then that undermines you. So it's always a good idea to start with questions. Lead with questions.

Yeah. Come from a place of curiosity. I love that. Let's go over some questions that my followers have for you, Maya. And the first one is from Ankita. She says, hi, I have an interview coming up and I'm currently working at a large company, but I'm trying to leave at almost the two year mark. I'm expecting the question of why do you want to leave so early? How do I best answer it without sounding too vague?

So I would not consider two years too early or super early, six months. Yeah, you're going to get a question, why are you leaving so early? But two years, a lot of people have learned some things. They figure out maybe this role isn't the right fit for them.

So.

So I don't think it's a big deal unless you don't have anything to show for your time there. If you spent two years somewhere and you haven't, you know, in our industry we'd say, I haven't shipped anything, don't have any business impact to reference, that's gonna be a problem. What were you doing for those two years? But if you've spent two years somewhere and you've built some things, you have some accomplishments to show, then find a better job. That's totally normal in this economy, especially in tech. My field, we, you know, two years is not early to be job hopping, in my opinion.

I agree. And the way that I would answer this question, the way that I would Answer any question that you're nervous about. The answer or you're not as confident about. The answer is give a brief answer and then take control of the conversation by asking the interviewer a question. So here's an example. If. If they said, oh, you've been at your job for only two years, why are you leaving so soon? I would say I've grown a lot. These are the goals I've helped the company reach, the impact that I've had, the changes I've helped implement at the company, and I'm ready for a change. Your company stood out specifically to me for these reasons. And I have a question for you about X, Y and Z. So if you're not as confident, just give a brief answer and then lead with a qu. Or finish with a question. So then they have to talk and they can't keep drilling into you like, well, we like our people to stay longer than two years. Are you going to leave us after two years? So that's.

I totally agree, and I did a fair amount of hiring in my previous role. And the other thing I would add to that is, regardless of the circumstances under which you're leaving, never bad mouth the employer that you're coming from. So whether or not there's probably things that you're not happy about or you wouldn't be leaving, you have to make it about future opportunities, not bad things from the company. You're leaving because that, as a hiring manager is a huge red flag, because someday I'm going to be in that position and you're going to be leaving me. And what are you going to go out there and say about the company that you're trying to get into now? Are you someone that's going to complain a lot and make a big stink about things, or are you just going to move on to the next opportunity and not bring a lot of drama with you? So I'd say two years is not too short. You're looking for more growth, new opportunities, new context, new industry, new challenges. Not my manager sucks. Not. No one's put me on a cool project in a while.

Everybody kept eating my sandwiches in the break room.

Yeah, none of that stuff.

One of the best managers that I have had, he used to ask in interviews, he'd be interviewing somebody and he'd say, what were you not getting at your current job that you'd be looking for in your next job? Because there's obviously. I mean, the elephant in the room is you're obviously leaving your company for a reason. Let's figure out practically and objectively if that thing is at our company. Because if it is, it might not be a good fit for you.

Yeah.

Yeah, I love that. Okay, ready for the next question?

Yeah.

Next question is. This one's from Joshua. Joshua says, I'm interested in getting into data science, but I'm not sure which of my skills are relevant. I have zero coding experience, but I'm a fast learner. Can you give me some advice?

Yeah, I have a lot of thoughts on this. Data science as a field has changed so much. Ten years ago it was barely a thing and now there's boot camps, there's PhD programs in data science, there's tons of data scientists out there and it's kind of a hard thing to define too. The role has changed a lot. So I'd say if you're interested in getting into data science, the most important thing you can do is make sure that you have a good grounding in software engineering, especially in tech. There are data scientists out there that are going to be building models for companies kind of more in house. And you may not need quite as much software engineering experience, but in my experience, the more competent someone is at being an engineer, we call them full stack data scientists. So data scientists that can not only build the model and apply the model and measure how effective it is, but can also build the pipeline that they need to get the data from where they need it in a database or a pipeline and help build the rest of the user experience around it. They're going to be a lot more effective at their role and they're going to be a lot more valuable to their company. So that's a big one, is to really lean into software engineering, machine learning engineering, kind of that as a, as a baseline, and then add data science on top. And part of the reason for this is that 10 years ago data science was a lot of building fancy models. And so the data scientists would get the data and then they would kind of, you know, build their own custom thing to make predictions over X, Y and z. But now in the field a lot of that's being done by other people and the models are often offered as open source models. And so you go on hugging face and you just like grab someone else's model that built a cool predictor for this thing and apply it to your problem or, you know, OpenAI. All of these LLMs, large language models are a great example. Like no one should be building their own large language model right now. You should be using any of the tools that are out there. Claude GPT4 llama put out by Meta Any of these tools, like, you don't need a data scientist to build those, you just need to apply to your problem. Maybe you fine tune it, maybe you point it at a vector store. That's a lot of engineering skills, not a lot of data science skills. As more open source models come out, as more of these tools become available via API, the core skill set of a data scientist like statistics and modeling and model fit and stuff are going to become less relevant. And the skill set of software engineering and being able to modify someone else's model to fit your use case is going to be a lot more relevant. Now you still need to be able to figure out, is this solving my problem? Does this model fit for its application? Are the predictions good? Or is the thing that I'm trying to do with it working? And that's a lot of critical thinking, frankly. But invest in the software engineering skills more so than the statistical modeling and the kind of deep model building skills that were a lot more relevant five years ago.

Okay, okay. There's a lot to unpack there. I want to tell you first that I love the way you speak because I just learned what Pipeline LLM and Full Stack mean and open source. So the way you talk, you talk about buzzwords, but you also like give me context so I know exactly what they mean. So I love that about you. Second of all, if somebody has just time and $0 to spend on this, are there any bootcamps out there where they can learn on their own for free?

Absolutely. There is so much content especially so the language you should be learning is Python. Python is super common. It works for the backend engineering, the machine learning engineering. It can build models in it. It's just like the most useful tool in my opinion for data science. And there's so much documentation, there's so much good help content out there. Python's a really accessible lang and there's a lot of great tools that you can do to kind of learn along the way and build those skills. And so one of them is, gosh, I'm forgetting Replit offers some training. And what's cool about Replit, I used it recently, is they have a lot of training for any sort of thing that you want to do. So introduction to Python, I used it to like deploy my first generative AI app, but they offer the full stack experience and so they will host your stuff for you as well. They have Gradio, which is kind of an interface tool built in so you can build Your own web app. And this is a really cool way to do it, because then you have something to show an employer. Here's a thing that I built.

Yes.

So what I built with it was a chatbot. And in fact, when I joined my current company, I was able to show a demo of a chatbot that I had built, and everyone was like, whoa, that's so cool. It took me, like, you know, an afternoon because Replit did such a good job with the onboarding, and all the tools are super accessible and the documentation was great. And so invest in one of those that is both going to teach you the skills and give you the infrastructure to deploy something that then you can put on your resume and put a link. You can link to your GitHub profile. You can link to a cool demo you built of a tool that's going to indicate to a hiring manager, not only do you know how to code a little bit, but you also understand, when is this useful? What can I do with this skill? And being able to show all the way through to. I built a little interface that, like, is now a chatbot that's an expert in this one thing that I made it an expert in. It's so useful. So Replit's great. I think there's a free version and then there's a paid version that's like $7 a month. So it's not. It's not very expensive. And it comes with all the learning in there. I think the learning's free. Another tool someone I know recently used to learn SQL is Data Camp. Datacamp may be paid, but it's pretty cheap. And datacamp's great because they have a bunch of different lessons and a bunch of different languages. They have practice coding questions. If you're going into a coding interview, they've got all sorts of prep for that. It falls into the same thing as practicing the speaking interviews. Practicing coding interviews is so important because then you get there and they're like, all right, write me a loop that's going to change all of the letters, you know, that aren't vowels to vowels or, you know, some arbitrary challenge to make sure that you know how to code. And Data Camp will have prepared you for some of that stuff.

So, okay, so you can do it for free if you're highly motivated and you have the time and cool.

Yeah. Coding is one of those things you can absolutely teach yourself. If you're dedicated and you're committed enough and you have a good growth mindset, like, no one is going to be good at Coding, the first time they do it, it is going to be really confusing and you're going to go, what the heck am I getting myself into? Am I a foreign language? Yeah, it's a foreign language. Am I stupid? I'm like staring at all these letters and I don't know what they mean. But if you stick with it, you will get better. I guarantee you will get better. Watch those help videos. Ask ChatGPT to explain code to you. Ask ChatGPT to write you simple code and explain it and you can absolutely get better. And I think that's one thing that it's just a matter of dedication and grit and time. The data science side is a little bit different in that there are some kind of methodologies that you need to know. You'll need to kind of understand what is the model supposed to be doing? How will I know if it's working right? Under what conditions do I use each type of model? But there's also a lot of courses out there that'll be helpful for that as well. So you don't have to go sign up for an expensive boot camp. You don't have to do that. If you are dedicated enough, you can absolutely teach yourself to code and you can probably teach yourself a lot of the relevant data science concepts that then you can learn more when you're on the job. If you have a good mentor, that's awesome.

Good. That makes me feel optimistic. It makes me feel like no career is out of reach for anybody. You can do it if you want. And I like what you said about doing a project like a DIY thing at home. And then you can put it on your resume. You can talk about it or demonstrate it, or bring it to an interview. I love to see when people do that because it means that, oh, you did this thing outside of work because you're passionate about it or because you're so motivated that you spent your free time doing this and you can talk about it. That's really impressive. So if you're thinking about doing something like this, where you're going to self teach or go at your own pace type of boot camp course, try to do some sort of tutorial or DIY project that you could put on your resume. Because Joshua, if he does everything you're saying, what would his resume look like? He would have to. If he doesn't have any data science or coding experience, he'd have to just put projects on there. But that's okay.

Yeah. The other great thing about that is because data science is such a Fast moving field. As a hiring manager, I look for someone that's going to stay on top of the field and it's going to take the time to learn new skills and teach themselves what they need to know and adapt to the changing environment. And, and so when you do that on your own time, when you do that as part of your learning, you indicate that you're capable of that, that you're interested enough that you know how to teach yourself new skills and go seek out the right tools for that. And that is frankly a lot more valuable than someone who maybe got some fancy degree but then like never updates their skillset. They like graduate and they're like, great, I have a fancy degree. But then in 10 years, you're using models that were deployed 10 years ago and the field has like 10 vastly changed out from under you. So having someone that's self taught, that's driven to learn the new technologies, to learn the new approaches is really valuable. And the other thing that showing a project is important for and useful for is it shows that you know how to think about how do I apply this? And if you do a novel application, that's even better, right? You can do some out of the box. I made a chatbot that can answer these types of questions. But if you figure out how to use that technology and apply it to an interesting problem that no one's done before, that's really going to stand out to a hiring manager. Because a lot of the data science job is figuring out where do we use data science. This has been a lot of my role in the past and now is like, here are a set of problems. Where can data science and AI be impactful? What should we invest in? What kind of problems could it solve? How can we innovate with this? And certainly you could get a role where your manager assigns you. You know, we need to predict who's going to churn from our website. Okay, you go in and do that. And that's certainly a valuable application of data science. But what's potentially even more interesting to me is someone who can say, hey, I noticed this thing over there and I think we can solve that with generative AI. And I built a little demo of it. So if you can do that while you're applying for jobs, that's really going to stay that out.

Yes, I love that. All right, are you ready for the final question? This one's from Rachel. She said, I love my job and I'm really good at it. I'm a software engineer for a mid sized company. Recently my manager asked me if I'd like to have a team under me and become a people manager. I'm not sure if I'll get to still code, but I would like my career to progress help.

This is a great question, and it's something that I think a lot of technical people struggle with because most technical people like building. They like quiet heads downtime, they like making something work and pushing that code and delivering it and seeing it work in the app. And when you become a people manager, a lot less of your job is building. And so if you find building really energizing and you find, you know, leading less energizing, there are ways to do that, to continue to advance your career as an individual contributor, to continue to rise into senior and then staff, technical and principal. And we have some of those at our company that are just. And I've got on the leadership team two principal engineers that don't want direct reports but still report into the CTO just like me and have a similar level of influence and leadership. And they don't want people under them because they really like building. But there are going to be some companies where in order to rise, you do need to take on leadership, whether it's from a kind of tech lead perspective, which you'd still get to build a lot, or having actual direct reports. And sometimes you're not going to find that energizing like people management can be really draining, especially if you have challenging people reporting to you or if you.

Don'T like giving feedback, which is a integral part of being a manager. That's something that. Or delegation. Delegation and giving feedback are two of the hardest things that a lot of leaders have to do.

Yeah. And so figuring out, you know, if you, if you want to stay hands on, if you want to stay technical, you can go to a company where there's a career path for individual contributors to continue to rise in the organization and you're going to cap out. You're not going to be a chief technology officer if you don't want to be a people manager, but you can get pretty high up there and you can still make a good salary rising in the ranks as an individual contributor and just get really valuable that way. If you want to try people management but still really want to remain hands on, have a small team to start. When I was at my previous company, I had a big team and I wasn't very hands on. And that was one of the reasons that I wanted to go back to startup is I miss coding, I miss building myself I miss prototyping and now I have a smaller team and so I'm able to spend a day, a week hands on building myself again. And it's energizing, but it's not all of my time, which I wouldn't really want it to be. I like the strategic part of my job too and thinking about what we should be building. And I like leading people. So being able to have a small team has given me more of that flexibility and being in a role that that's what they're looking for from me is a bit of both has been helpful there too. And then the last thing I'll say about this is a lot of people, especially in engineering, go back and forth. I know a number of people who have tried people management and then go back to being a, you know, senior individual contributor and then maybe go back to being a people leader again. Like this isn't a. You pick it once and you're never gonna be able to change.

I've heard somebody say that like once you go to people management, you can't go back to technical, but I don't think that's true.

I don't think that's true either. And the skills that you gain as a people manager are useful in your technical role too.

They're useful in your daily life with family and friends too. Giving your mom feedback. Giving my mom feedback, yeah, totally.

I always think that someone who's been a people manager has a much higher emotional IQ on average than someone who hasn't been a people manager. And that makes them more valuable as a senior member of my team. So it's certainly not a bad thing. As long as you stay hands on and you keep your skills fresh, it won't hurt you.