155: This Teacher Became a Data Analyst AFTER a 25-Year Career (Cynthia Clifford)

This is Cindy Clifford. And Cindy was a teacher and educator for over 25 years until

I reached a real burnout stage with teaching and I knew I needed to do something different.

And honestly, can you really blame her teaching is really, really hard in the first place. But Cindy was not only a teacher, she was an international school teacher and endured some pretty crazy thing.

I was stuck in a military coup in Myanmar, and then I went to Vietnam and I got stuck in Covid Lockdowns. I spent a year teaching online without being able to leave my neighborhood.

Yeah, that's not fun at all. Being a teacher is hard, but here's the truth. Teachers make great data analysts. In fact, most teachers are already kind of analyzing data one way or another. Whether they realize it or not, teachers

are constantly evaluating and assessing the situation and our problem solving and data analysis really is about problem solving and communicating the results of the problems you've solved.

In this episode, Cindy and I will explore her data career story and what helped her leave a career of 25 years. Ultimately become a data analyst at a company like Impossible Foods. Thank you so much for subscribing to our show, and let's go ahead and dive into this episode. Alright, Cindy, you studied engineering in college and then you had a 25 year career in teaching all over the world. What made you wanna become a data analyst?

I wanted to become a data analyst because, well, partly, and I know you've had other teachers that in the program, I reached a real burnout stage with teaching and I knew I needed to do something different, and I'd known that for a while, but it really reached a height, as you said, I was teaching all over the world. I was stuck in a military coup in Myanmar, and then I lost my job, and then I went to Vietnam and I got stuck in Covid lockdowns. I spent a year teaching online without being able to leave my neighborhood. None of that was good for my mental health. And I came back to the US after that summer and I said, alright, you gotta figure it out. You absolutely have to figure out what you wanna do. And I spent the summer informational interviewing. I met. Kind of everybody under the sun made connections on LinkedIn, asked them if I could ask about their job and what they did. I first thought I would want to do the kind of things that a lot of teachers transition into, like, uh, instructional design or learning and development in a corporate environment, and. Still realized that that wasn't the direction I wanted to go, and I, you know, I taught high school math and statistics. I always, the math was always my favorite subject. And data analysis started to make, make a lot more sense. I reached out to a, a former colleague who's still a friend. Who had already made that transition and he's now a data scientist. And he and I talked a lot about what I needed to learn and what some of the ways to learn were. And I decided I was gonna go for it. So my last year of teaching overseas in Vietnam, I spent weekends and evenings. I started with the, the Google Data Analytics certificate, and that confirmed that I wanted to go in that direction. But when I found you, I was really glad because I knew that I wasn't really, it was like taking little quizzes and I'm, I'm a good student, I can do that, but I knew that I wasn't really learning. To do things in a way that was gonna help me find a job. So

it makes a lot of sense 'cause my mom's a teacher. Being a teacher, I mean, obviously you're making a difference in kids' lives and that's very meaningful and we appreciate all of our teachers. But being a teacher kind of sucks a lot of the time for many reasons. Like you said, long hours, low pay, and it can be just like. Very stressful and, and fatiguing, so it makes sense. You, you found something in, in data analytics. You're like, okay, I'm good at math, I'm good at statistics. Let's do, let's do this and find a little bit more of a calmer career. Start off with the Google search. I had forgotten about that and I. And I like what you said, it would like confirm that like, okay, this is something I wanna do moving forward, but didn't like, feel like it prepared you for a job. Do you remember, I, this is going off script here, but do you remember how you found me? Like this was, this was a while now 'cause you've been in your, in your career now for what, almost two years? I think so. Yeah. A

hundred percent no. But I know that I had started networking on LinkedIn and reaching out to various people and making connections and comments. None of it's supernatural to me, but I was already doing that and. Following people and finding people who had made the transition to data who were formerly teachers, and somewhere or other I came across your. One of those come and listen to the, my program, you know, talks that you were running, what you were saying made a lot of sense. You know, I am kind of cheap and I was like, Hmm, is this like legitimate or is this, you know, one of these 'cause so many sort of scammy things on LinkedIn. But I somehow, I trusted and I'm glad I did.

Good. I'm, I'm glad you did as well. Like you said, you kind of spent, uh, that last year of teaching ramping up to, for this transition. And I remember, I remember seeing your, your comments in the community late nights, I guess for, for me or or I, and for you, because, uh, of the time difference, we usually have live calls like at 7:00 PM Eastern Time and for a while I, where were you and what time was it? 'cause you came to a lot of our live calls.

I wasn't able to go to a lot of those. I was in Vietnam and it was like. Seven in the morning for me, but I was already on my way to work.

I, I remember you coming to a couple in, in the mornings, um, and you might be, well that's

to then after daylight savings or something. Ah, then it became six in the morning and I could go for an hour or for 50 minutes of it, and then I had to leave.

Perfect. You were very dedicated and you, you did, uh, a lot of good research. Were you nervous to make this transition though? Because you had been teaching for over 25 years where you're like, can I really just reinvent myself again?

I was definitely nervous, but I was also fairly feeling fairly, like I just couldn't go on teaching and I had decided I wanted to move back to the US and I did not want to be a teacher in the US 'cause I thought that would've even been worse than being a teacher overseas. Being a teacher overseas had been really good for a long time until it, it wasn't, I didn't know exactly how long it was gonna take you to find a job, but I had saved up transition and felt like I had a bit of a buffer that if it also felt like, 'cause I was already older, like it was sort of like, well, it's not now when like. Like, I, I have to do it. Like, so

I love that attitude though, because I feel like a lot of people would just be like, ah, too late. You know? Um, but like, life's long and you're also a very healthy person. We've talked in the past, uh, you know, about, uh, you try to, try to eat healthy, try to exercise, stuff like that. I. Like life's long. Like we have an opportunity, you know, we, we have to work, we have to go to work. It's a big part of our lives. Like, you know, you're spending probably like around eight hours a day working everyone, right? And you want to be doing something you enjoy. You don't wanna be miserable. Like if you're miserable now, like in 1, 2, 5, 10 years, like, what's going to change if you don't make a change? And, and even if like the best time to plant a tree was 10 years ago, the next best time. Is today. So I just wanna commend you for being brave, because I think a lot of people wouldn't be brave and be like, ah, oh, well I, I tried.

Yeah. No, I, I, but I, I am, I think in a lot of things, I have that attitude that it's never too late to try new things. I mean, I learned to cross country ski this year and working from home in, in a cold climate like Vermont, I. Spend too much time indoors in the winter. So I decided this year that I was gonna learn to do a pull up and put a pull-up bar outside my right where my office door is. And every time I leave the room and to come back, I have to practice a pull up. I can now do a pull up. Like, it's never too late to, to just try. Like, otherwise you might as well, like you said, just curl up and it's done.

Be miserable. For those of you, uh, for everyone listening, you can definitely tell what type of student, uh, Cindy is because she is ferocious. Uh, you know, she's, she's willing to do, she's dedicated, she's, um, consistent where she's like, even if it's just one pull up, you know, I'm just gonna try to do that one pull up. Or if it's just a half, I'm gonna do the half pull up. And that's how she was as a student inside the accelerator program as well. And I'll have to say, you kind of had to be, because you were transitioning from obviously not a tech field, like teaching is not a tech field. And I'd almost argue that being in education is almost like a non-corporate field, right? Like jobs aren't the same in the education world as they are in other industries. Just because like it's, things are just different. Like LinkedIn's not a thing and you get a lot of jobs from your district or this and that, or like you're. I don't know who, you know, your principal or whatever, plus like you weren't even in the us you hadn't even been really in the US for a decade. And so, you know, you join my program, you're like great Avery's, SPN method I'm in. And like the third part of the program, 33% of the program is networking. You're like, uh, I'm a teacher who's been living overseas for a decade. My network is, uh, maybe not the best ever. So I just, I just wanna give you like some credit for one being like ferocious and battling through that. 'cause once again, a lot of people I think, would use that as an excuse and give up. But like how did you network with like this education and international background that really maybe wasn't super helpful for you?

Well, I had actually found a program before I found yours, which is how I started getting into LinkedIn. I. That program has is something that helps teachers transition out of teaching and there's a bunch of lessons including networking. And I had been taking action on that before I met you. I was joining data groups and I. Especially looking and searching for people who were former teachers, and particularly if they were former international teachers and looking for connections. And then I would just reach out to them and ask them if, well, they had done, made their transition and started building a network. And the more. People that, you know, then you start getting connected to more of them and it, it did start to grow and it, it grew a lot more in the program 'cause other people would be connected to somebody and then I would connect to them and then I would see people on their feet and I started making comments and I actually really grew a pretty good network of people. But I didn't have, it was more when I was looking for jobs, I didn't have people that I knew that worked inside of a company, maybe with a different kind of role that could help give me a, an internal referral or, or that, that's when I. It was more of a challenge. It wasn't so much a challenge networking and meeting people as it was that I did. I didn't have INS any place. And I remember one of the, you were trying to show us during the accelerator program that we all knew people, and you were like, I want you to take out your phone now, and I want you to look at who you like Glass spoke to and. Do you know what their's like, and people were saying, oh, my cousins, or my, you know, this, or my, and, and I'm like, oh, I spoke to an independent farmer in Laia.

Not the most data-centric role I would imagine.

So that was where it was more challenging, was in the job hunt part, not the meeting people online and connecting.

So how did you, how did you overcome the, the job hunt part? Or, or how did you end up landing your, your first, uh, data role?

I looked for lots of kind of billboards and job sites that weren't necessarily just LinkedIn, like I think I'm the one who told you about the tech Jobs for Good site, and I followed lots of, I thought that my best bet initially would probably be to get with some sort of an education company as a data analyst, so I was following. Ed tech, blogs of various kinds and job postings through there, and I applied to a lot of jobs. Like I was more successful getting interviews when I applied to jobs from some of these kind of less known. Venues. Um, I don't know if I ever really got an interview from anything I applied for on LinkedIn, even if I applied on the company website, but I'd found the listing on LinkedIn. I, you know, I just, I didn't have the corporate background. I didn't have the connections, I didn't have internal referrals, I had nothing. So I had to essentially called, call everything and always sent cover letters that were very tailored. To the job. I always researched the company and I probably applied to fewer places per week than many of the students in the program. But I only applied to jobs that I thought I was really legitimately, pretty qual like that. I, there was a reason why somebody might look at me even with my limited experience.

That makes a lot of sense. I think most people are on LinkedIn and only looking at at LinkedIn jobs, which by the way, um, I don't know if you have seen this, oh, you have seen this, but I have find data job.com now and premium data jobs, which are trying to pull, help people find jobs that aren't necessarily listed on LinkedIn. So now you could have used those jobs boards, but those didn't exist back then. You're applying to jobs you think you're a good fit for, you're looking at job boards and job listings that maybe other people aren't. And then. You're, you're trying to stand out because you're sending, you're sending cover letters that are, that are quite tailored, and then is that how, how you and

following companies that, that, that I, you know, ahead of time and commenting on, on that company's posting and those things as well.

Okay. And how did you land your, your first job with, uh, with Impossible, right, which is basically they make the, the vegan meat.

I found that job on tech Jobs for Good, and I wrote a really tailored cover letter because it was very clear from the job description that cultural fit was really important. I made sure that they knew that I tried impossible foods, that I, you know, made ccad with the impossible beet for my vegetarian sons. That I really knew what I was, that, that it's an important mission to try to reduce some of the greenhouse gases from animal production and that I'm behind that mission, and I think that's why I got an interview.

That's really cool that you, you were really tying like, you're like, Hey, I'm not just another, you're not just another company to me. I'm not just another candidate to you. I think this is a good culture fit. We should also mention that like you, you live in Vermont, it's not like the biggest corporates tech hub of the United States, so there's not a ton of data jobs in Vermont, so you are also looking for remote, which, which obviously makes things, uh, a bit more, more competitive. Um, so you apply to this, this job as a remote job. Do you remember what the interview process was like at all?

I had a screening with the the, with the recruiter who passed me on to the hiring manager, and after I met with her, I had four more interviews. With different people in either the team or a team I might interact with. They were all half an hour. There were two back to back and another two back to back. So I met altogether with, besides the recruiter, with five people. And I do know that. They speeded the process up a little bit because they asked me early on if I was close to an offer or I got an offer from anybody else to let them know. And I did get an offer from, and now from, uh, an agency in Vermont, a state agency. So I was able to sort of parlay that. I mean, and it was legitimate. I mean, I did get that offer, but. It was, I was able to sort of put pressure and move the process along.

Okay. And do you remember the interview being hard? Like were there difficult technical questions? Were they talking about stats or sequel?

No. All really kind of cultural fit and behavioral questions and I.

I, I find a lot of our students somehow get internship or not internships. I find a lot of our students get interviews that are, are more behavioral and, and less technical, which, which I think is, is quite interesting. Okay. You're there for a bit. And what type of tools, uh, are you using on the job?

Mostly Google Sheets slash Excel and creating templates of various kinds so that I could take data that I would, would access from outside databases. I could take it and plunk it in and it would automatically update. I had, I'd created a bunch of these sort of tools. I had to prepare the weekly sales and share report, which went to the executive leadership team. That was all in PowerPoint, but I would have to pull pictures out of the, these templates that I had made. So I used sheets, I used PowerPoint, and, and then in the consumer packaged goods industry, there were a whole load of companies. Numerator, IRI, Nielsen, MPD, they all point of sales data, if you think about it, is a massive data set. And so they kind of aggregate all of this and they have their own proprietary systems and you companies pay subscriptions to access this data. And I would have to do the data pulls. I really did pretty much all the data pulls and supported the sales. Team and created these reports and the logic of these systems was quite SQL based, but it wasn't SQL because there was an, you know, an overlay. But I would have to, you know, pick this and group by this and wasn't highly intuitive. It was actually pretty hard to learn some of these, and there were like maybe three or four different systems I had to learn and one was for food service and one was for. Something else and one was just for Kroger and both was, and each was different.

I think that's important to to note because it's not like, like in the accelerator that we can cover, you know, this, these types of tools. And honestly like most jobs have some sort of proprietary data software or industry specific data software that like. Really you don't even know exists until you're there. And even if you did know exists, you probably really couldn't access it, uh, unless you work for like a corporation. So it's, it's like that's exists at every job I

was interviewing. They told me that I, part of the job I would have to access IRI data. So I looked up that thinking, all right, well, I'll go see what this is like before. And to be even to get, be even a researcher and get access was over a thousand dollars. So I was like, well, I guess I'm not gonna access that.

That's, that's how that goes. Uh, that makes a lot of sense. And you're wise for like, trying to look it up beforehand and, and be prepared. That was, that's really cool. Okay, pause for a second. Uh, I didn't really think through how we wanna transition to your second job. Uh. I can say you're just there for a while and then like you ended up getting into, and they had had a reduction in

force and they moved. Um, and well that what, what they actually did was they reclassified all these jobs as hybrid honest truth. They did that because they wanted people to quit, but Yes. Um, because they had then ended up with a big layoff shortly after that. So I think we can just sort of say there was sort of. They, they transitioned jobs and there was a reduction in force.

Okay, so you're at Impossible Foods for a while. And then they ended up kind of reclassifying a lot of jobs to, instead of being remotes, to be hybrid and, uh, their, their offices are not in Vermont. And so you ended up, uh, not being able to work at them and any further. And then you had to find, uh, a new data job. How did you find the second data job?

Well, I actually, this time I had several internal referrals for things within the consumer packaged goods industry. So I was pursuing those. I also was pursuing things I'd found on LinkedIn or on your job boards or, and I gone. Actually the final round four times and didn't get the job. It was exhausting. I mean, you know, done the project, done a panel presentation, like all sorts of stuff for several jobs and was feeling pretty down. And I'm not, and somebody I know from LinkedIn and I think from this program, but, uh, okay, so someone from the program who I'd connected with and we've had coffee chats with. And continued to keep in contact with, 'cause I always appreciate her thoughtful comments on LinkedIn. I had chatted with her, uh, because she was looking for a new, a new role or had just gone through the process of looking for a new role and I let her know with the position I was in, and she actually said to me, I just interviewed with a company and I. They offered me a job and I'm not taking it. And she said, not because it wasn't a good job or a good company, but she had personal reasons for why it wasn't the best fit for her circumstances at the time. And she said, if you'd like, I'll, I'll write to the hiring manager and recommend you. So even though she had turned this job down, she wrote to the hiring manager and or to the, the recruiter and told him that she thought I would be a great fit and I ended up meeting with him without actually even applying. And he then set me up to interview with the hiring managers also before I'd ever filled out an application on the site. And. Because I know that after, after meeting with the hiring managers, the recruiters said, you know, we need to have you fill out this application. And she was great because she had given me a little bit of heads up about the sorts of questions they were gonna ask me in the interview as well. So I was able to be very prepared. The interview was. With the hiring managers. There were two of them. It was a, it was a good interview. They were both really thoughtful. It was clear that they had a set of questions. They were growing the team substantially. A, a year before I joined, this particular team had maybe five or six, maybe seven people, and now we're 20 and they'd hired, I was one of the last of this big explosion of hires. The. Questions were a mix of, I wouldn't say highly technical, but they did ask what I, I mean, this is in the energy industry. They asked, you know, what I knew about how power was generated. They asked if. They asked questions about what was the most complex sorts of things I've ever done with Excel, but they also asked behavioral questions.

Well, what's cool is, you know, you have been working as an international teacher for, for a while, but you studied engineering in school and you even had an engineering job, you know, out of college for a little bit. So I'm sure that like not only having this awesome, basically internal reference to the hiring manager. Also being like, Hey, look, I understand engineering principles. I think that probably sets you apart compared to most analysts.

Oh, for sure. Because when they asked me, you know, what I knew about how energy was generated, you know, you know, I was like, well, I. I just spew off an answer like, well, there's lots and lots of ways of, you know, getting, you know, converting sort of potential energy to kinetic energy and getting that turbine moving and getting, you know, and like I, you know, I went on and thought it on, I think, and, and it's been really useful in my work there to have that sort of understanding all of the analysts. Take Workday courses all on things like HVAC systems and, and when I was an engineer, you were chemical, I was mechanical and thermodynamics was actually. My best subject engineering job I had when I was an engineer was in energy conservation. So even though it was quite a while ago, those fundamentals are in there and it's helpful now.

Very cool. I wanted, I wanted to ask earlier, like, you know, even though you were a teacher. Did you find that you had transfer transferable skills into analytics, and obviously sounds like in this case your, your engineering background stuff was, was transferable. Were some of your teacher skills transferable as well?

Oh, for sure. I think that, I mean, in a variety of ways. In my current role we are, we do a lot with statistics. We look at the statistics of models, are these appropriate models? Are is the, are the residuals normally distributed? That sort of thing. And having taught higher level math and AP statistics, I've been able to actually contribute to my team. By creating, we have team weekly team meetings that are team trainings where people will present things and I presented on, oh, here's the Durbin Watson statistic and auto correlation, and what does it really mean? And used really simple examples that. That aren't necessarily embedded in the energy context, but are maybe embedded in ice cream shops and beaches. Everybody can understand and people have said that they've been really helpful. I, knowing the statistics has certainly been transferable and, and, and math modeling, I mean, understanding variables. I, you know, I was the calculus lady, but other skills that all teachers have are really transferable. Teachers can learn new things. When you're a teacher, you. You get thrown into, you know, they'll be like, oh, we have a new software that we're gonna use for, you know, great. And they'll bring one person in and do a two hour point and click and then they'll be like, off you go. And teachers figure it out. 'cause they have to, I've been surprised in the corporate world actually, how much time they give you to. Learn things. 'cause when you're a teacher, they don't give you that. I think things like knowing how to do a presentation in, in Impossible Foods, I had to make PowerPoints. Like I actually, at one point, I, I looked at the PowerPoint and I was like, you know, we just come out with these new company color branding and like, is is there any chance I could like redo the template for the PowerPoint? So it's very cohesive, like, and what I made then ended up saw it showing up in. People much higher than me kind of taking my templates and using them because I, I know how to make a power one.

There's, there's all sorts of different ways that teachers can, you know, transferable skills. Even, even when you said earlier when you were talking about some of the statistics and, you know, maybe not in energy, but like in ice groups and stuff like that, teachers are, are good at explaining things and really like what you're actually doing as a data analyst. A lot of the time is just telling business people or higher ups what's happening in the business from a numbers perspective. And so as a teacher, you're, you're, you've been trained to communicate clearly, whether it's in a PowerPoint or, or orally to say what's going on. Uh, and like you said, also, teachers are fantastic students. And like you said, at Impossible Foods, you had to learn this like proprietary database system that like you couldn't really learn on your own beforehand. At your, your current company. We haven't talked about it, but you use this software called jump. JMPI really like jump as well, but it's not like something that's really, it's not super common. It's, it's an awesome tool, but it's not super common and it's quite expensive. Um, if you try to get like a license on your own, it's gonna cost you about $2,000 a year. So it's not like something you, no one really learns, jump on their own and then gets into a job. You always learn jump. On the job, and that's something that teachers are gonna excel at. They're gonna be great. And, uh, to be honest, especially with how AI's going right now, like we're gonna have to keep learning new things year after year after year as a data analyst for the next two or three decades.

Well, I use AI a lot of times in, in my role when I'm, I'm doing some of the Excel based work and I know I wanna maybe. Pull something from this tab over to this one and, and aggregate it by the week. And, but when I, if I have blanks, I don't want them to show up as zeros. I want them to show up as nas, then I will put the appropriate information, describe the situation and put that into ai. 'cause you, you can't obviously, you know, company spreadsheet, you know, with chat GPT, but, but I will put in the relevant information and. I ask for the, the code, and it's really good at giving me very succinct ways to do some of the things I need to do.

I, I love that. It's just AI is not replacing us. It's just helping us work faster. Um, I think that's really cool. Has anything, has anything really surprised you as a data analyst? Like maybe something you didn't realize that, that the job would be like? I.

Well, I would say that my first role, I was surprised by a lot of things, but a lot of that was more just the way that corporate works. Coming from a teaching background, I, things are so different in teaching. They want you to get something done fast and it might not be the most perfect version of something, but if they say they want this, they, well, they'll get something and they'll get it when they need it. I found that I had that mentality and would be like, well, did you proofread this? Did you, I mean, like of course I proofread it, but did you check this? Did you run it by three or four other people and get their feedback? Did you do like for things that were supposed to be rushed and. Could end up being, we're gonna roll this new dashboard out, it's gonna take two months. And teaching it would be like, well, here it is, and like, you know, start playing with it and figure out what you can, if there's problems, let me know if there's problems, let me know. Be an issue. In teaching, it would be part of the process of how things work. And it seems like in the corporate world, it's all a lot slower. But it has to be right. Like they're not iterating constantly on the fly. You're supposed to do all these iterations and then say, here,

it's, it's, it's definitely a different world than, than teaching. Uh, for sure. What advice would you give to teachers who want to become data analysts?

The teachers are constantly evaluating and, and assessing the situation and our problem solving and data analysis really is about problem solving and communicating the results of the problems you've solved or, you know, every, like you said before, if, if, if they're sales data you're trying to explain to an executive, not, you don't need to explain that the. Sales went up, or sales went down. That's a, like a concrete number, but you're trying to dig into why and what other drivers are there that made that happen? Or in my current role, which are the variables that are gonna best explain, uh, best represent, allow us to create a model that will describe a company's. And there might be tons of different variables, but we're trying to come up with the ones like a really simple model that will still explain really clearly and teachers do the same thought process all the time. Why is Joey not understanding? This concept? What is going on? Is there a piece that's missing? Is there like all that back thinking and the, Hmm, let me think. Let me take a look. Does he know how to do this? Does he know how to do this? Does he know how to do this? Oh, and then he doesn't know how to do that. So somewhere there's this connection that Joey's not making or Johnny's not making. Teachers do that all the time, and they do it for rooms full of kids. And they finish the day and they ruminate over what went well and what didn't go well and why you're just applying that same skillset, that same sort of thought process to a new context.

It's problem solving at the end of the day, and teachers have always been good problem solvers. Uh, Cindy, you're one of the best problem solvers I know. Uh, and I'm sure, uh, your current company is super lucky to have you, and I was lucky to have you. As a student in, in the Accelerator. Thanks so much for coming on the show and, uh, sharing your story.

No, it was my pleasure. It was really good to catch up. Avery, you were wonderful to me and continue to be

good. I'm glad I.