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

Avery Smith: 00:00:00

This is Cindy Clifford.

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And Cindy was a teacher and

educator for over 25 years until

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Cynthia Clifford: I reached a real

burnout stage with teaching and I knew

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I needed to do something different.

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Avery Smith: And honestly, can you

really blame her teaching is really,

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really hard in the first place.

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But Cindy was not only a teacher, she

was an international school teacher

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and endured some pretty crazy thing.

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Cynthia Clifford: I was stuck

in a military coup in Myanmar,

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and then I went to Vietnam and

I got stuck in Covid Lockdowns.

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I spent a year teaching online without

being able to leave my neighborhood.

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Avery Smith: Yeah, that's not fun at all.

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Being a teacher is hard,

but here's the truth.

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Teachers make great data analysts.

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In fact, most teachers are already kind

of analyzing data one way or another.

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Whether they realize it or not, teachers

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Cynthia Clifford: are constantly

evaluating and assessing the situation

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and our problem solving and data

analysis really is about problem

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solving and communicating the results

of the problems you've solved.

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Avery Smith: In this episode,

Cindy and I will explore her

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data career story and what helped

her leave a career of 25 years.

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Ultimately become a data analyst

at a company like Impossible Foods.

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Thank you so much for subscribing

to our show, and let's go ahead

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and dive into this episode.

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Alright, Cindy, you studied engineering

in college and then you had a 25 year

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career in teaching all over the world.

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What made you wanna become a data analyst?

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Cynthia Clifford: I wanted to become

a data analyst because, well, partly,

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and I know you've had other teachers

that in the program, I reached a real

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burnout stage with teaching and I knew

I needed to do something different,

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and I'd known that for a while, but it

really reached a height, as you said,

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I was teaching all over the world.

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I was stuck in a military coup in

Myanmar, and then I lost my job,

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and then I went to Vietnam and

I got stuck in Covid lockdowns.

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I spent a year teaching online without

being able to leave my neighborhood.

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None of that was good

for my mental health.

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And I came back to the US

after that summer and I said,

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alright, you gotta figure it out.

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You absolutely have to

figure out what you wanna do.

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And I spent the summer

informational interviewing.

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I met.

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Kind of everybody under the sun

made connections on LinkedIn,

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asked them if I could ask about

their job and what they did.

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I first thought I would want to do the

kind of things that a lot of teachers

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transition into, like, uh, instructional

design or learning and development

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in a corporate environment, and.

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Still realized that that wasn't the

direction I wanted to go, and I, you know,

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I taught high school math and statistics.

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I always, the math was

always my favorite subject.

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And data analysis started to

make, make a lot more sense.

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I reached out to a, a former

colleague who's still a friend.

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Who had already made that transition

and he's now a data scientist.

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And he and I talked a lot about

what I needed to learn and what

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some of the ways to learn were.

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And I decided I was gonna go for it.

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So my last year of teaching overseas in

Vietnam, I spent weekends and evenings.

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I started with the, the Google Data

Analytics certificate, and that confirmed

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that I wanted to go in that direction.

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But when I found you, I was really glad

because I knew that I wasn't really, it

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was like taking little quizzes and I'm,

I'm a good student, I can do that, but

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I knew that I wasn't really learning.

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To do things in a way that

was gonna help me find a job.

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So

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Avery Smith: it makes a lot of

sense 'cause my mom's a teacher.

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Being a teacher, I mean, obviously

you're making a difference in kids'

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lives and that's very meaningful and

we appreciate all of our teachers.

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But being a teacher kind of sucks

a lot of the time for many reasons.

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Like you said, long hours, low

pay, and it can be just like.

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Very stressful and, and

fatiguing, so it makes sense.

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You, you found something

in, in data analytics.

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You're like, okay, I'm good at

math, I'm good at statistics.

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Let's do, let's do this and find a

little bit more of a calmer career.

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Start off with the Google search.

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I had forgotten about that and I.

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And I like what you said, it would like

confirm that like, okay, this is something

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I wanna do moving forward, but didn't

like, feel like it prepared you for a job.

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Do you remember, I, this is

going off script here, but do

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you remember how you found me?

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Like this was, this was a while now

'cause you've been in your, in your

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career now for what, almost two years?

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I think so.

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Yeah.

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A

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Cynthia Clifford: hundred percent no.

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But I know that I had started

networking on LinkedIn and

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reaching out to various people and

making connections and comments.

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None of it's supernatural to me,

but I was already doing that and.

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Following people and finding people

who had made the transition to data

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who were formerly teachers, and

somewhere or other I came across your.

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One of those come and listen to

the, my program, you know, talks

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that you were running, what you

were saying made a lot of sense.

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You know, I am kind of cheap and I was

like, Hmm, is this like legitimate or is

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this, you know, one of these 'cause so

many sort of scammy things on LinkedIn.

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But I somehow, I trusted

and I'm glad I did.

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Avery Smith: Good.

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I'm, I'm glad you did as well.

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Like you said, you kind of spent,

uh, that last year of teaching

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ramping up to, for this transition.

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And I remember, I remember seeing

your, your comments in the community

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late nights, I guess for, for me

or or I, and for you, because, uh,

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of the time difference, we usually

have live calls like at 7:00 PM

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Eastern Time and for a while I,

where were you and what time was it?

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'cause you came to a

lot of our live calls.

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Cynthia Clifford: I wasn't

able to go to a lot of those.

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I was in Vietnam and it was like.

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Seven in the morning for me, but

I was already on my way to work.

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Avery Smith: I, I remember you coming

to a couple in, in the mornings,

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um, and you might be, well that's

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Cynthia Clifford: to then after

daylight savings or something.

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Ah, then it became six in the morning

and I could go for an hour or for 50

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minutes of it, and then I had to leave.

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Avery Smith: Perfect.

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You were very dedicated and you,

you did, uh, a lot of good research.

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Were you nervous to make

this transition though?

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Because you had been teaching for

over 25 years where you're like, can

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I really just reinvent myself again?

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Cynthia Clifford: I was definitely

nervous, but I was also fairly feeling

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fairly, like I just couldn't go on

teaching and I had decided I wanted

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to move back to the US and I did not

want to be a teacher in the US 'cause

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I thought that would've even been

worse than being a teacher overseas.

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Being a teacher overseas had been

really good for a long time until it,

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it wasn't, I didn't know exactly how

long it was gonna take you to find

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a job, but I had saved up transition

and felt like I had a bit of a buffer

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that if it also felt like, 'cause I

was already older, like it was sort

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of like, well, it's not now when like.

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Like, I, I have to do it.

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Like, so

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Avery Smith: I love that attitude

though, because I feel like a lot of

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people would just be like, ah, too late.

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You know?

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Um, but like, life's long and

you're also a very healthy person.

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We've talked in the past, uh, you

know, about, uh, you try to, try to eat

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healthy, try to exercise, stuff like that.

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I.

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Like life's long.

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Like we have an opportunity, you know, we,

we have to work, we have to go to work.

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It's a big part of our lives.

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Like, you know, you're spending

probably like around eight hours

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a day working everyone, right?

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And you want to be doing

something you enjoy.

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You don't wanna be miserable.

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Like if you're miserable now, like in

1, 2, 5, 10 years, like, what's going

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to change if you don't make a change?

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And, and even if like the best

time to plant a tree was 10

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years ago, the next best time.

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Is today.

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So I just wanna commend you for

being brave, because I think a lot

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of people wouldn't be brave and

be like, ah, oh, well I, I tried.

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Cynthia Clifford: Yeah.

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No, I, I, but I, I am, I think in a lot

of things, I have that attitude that

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it's never too late to try new things.

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I mean, I learned to cross country

ski this year and working from home

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in, in a cold climate like Vermont, I.

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Spend too much time indoors in the winter.

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So I decided this year that I

was gonna learn to do a pull up

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and put a pull-up bar outside my

right where my office door is.

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And every time I leave the room and to

come back, I have to practice a pull up.

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I can now do a pull up.

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Like, it's never too late to, to just try.

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Like, otherwise you might as well, like

you said, just curl up and it's done.

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Avery Smith: Be miserable.

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For those of you, uh, for everyone

listening, you can definitely

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tell what type of student, uh,

Cindy is because she is ferocious.

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Uh, you know, she's, she's willing

to do, she's dedicated, she's, um,

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consistent where she's like, even if

it's just one pull up, you know, I'm

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just gonna try to do that one pull up.

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Or if it's just a half, I'm

gonna do the half pull up.

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And that's how she was as a student

inside the accelerator program as well.

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And I'll have to say, you kind of had

to be, because you were transitioning

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from obviously not a tech field,

like teaching is not a tech field.

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And I'd almost argue that being

in education is almost like

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a non-corporate field, right?

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Like jobs aren't the same in the education

world as they are in other industries.

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Just because like it's,

things are just different.

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Like LinkedIn's not a thing and you

get a lot of jobs from your district

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or this and that, or like you're.

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I don't know who, you know, your

principal or whatever, plus like you

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weren't even in the us you hadn't even

been really in the US for a decade.

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And so, you know, you join

my program, you're like great

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Avery's, SPN method I'm in.

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And like the third part of the program,

33% of the program is networking.

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You're like, uh, I'm a teacher who's

been living overseas for a decade.

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My network is, uh,

maybe not the best ever.

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So I just, I just wanna give you

like some credit for one being like

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ferocious and battling through that.

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'cause once again, a lot of

people I think, would use

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that as an excuse and give up.

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But like how did you network with

like this education and international

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background that really maybe

wasn't super helpful for you?

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Cynthia Clifford: Well, I had

actually found a program before

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I found yours, which is how I

started getting into LinkedIn.

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I.

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That program has is something

that helps teachers transition out

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of teaching and there's a bunch

of lessons including networking.

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And I had been taking action

on that before I met you.

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I was joining data groups and I.

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Especially looking and searching

for people who were former teachers,

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and particularly if they were

former international teachers

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and looking for connections.

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And then I would just reach out to

them and ask them if, well, they

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had done, made their transition

and started building a network.

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And the more.

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People that, you know, then you start

getting connected to more of them and it,

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it did start to grow and it, it grew a lot

more in the program 'cause other people

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would be connected to somebody and then

I would connect to them and then I would

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see people on their feet and I started

making comments and I actually really

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grew a pretty good network of people.

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But I didn't have, it was more

when I was looking for jobs, I

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didn't have people that I knew that

worked inside of a company, maybe

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with a different kind of role that

could help give me a, an internal

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referral or, or that, that's when I.

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It was more of a challenge.

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It wasn't so much a challenge networking

and meeting people as it was that I did.

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I didn't have INS any place.

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And I remember one of the, you were

trying to show us during the accelerator

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program that we all knew people, and

you were like, I want you to take out

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your phone now, and I want you to look

at who you like Glass spoke to and.

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Do you know what their's like, and people

were saying, oh, my cousins, or my, you

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know, this, or my, and, and I'm like, oh,

I spoke to an independent farmer in Laia.

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Avery Smith: Not the most

data-centric role I would imagine.

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Cynthia Clifford: So that was where

it was more challenging, was in

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the job hunt part, not the meeting

people online and connecting.

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Avery Smith: So how did you, how did

you overcome the, the job hunt part?

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Or, or how did you end up landing

your, your first, uh, data role?

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Cynthia Clifford: I looked for lots of

kind of billboards and job sites that

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weren't necessarily just LinkedIn, like

I think I'm the one who told you about

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the tech Jobs for Good site, and I

followed lots of, I thought that my best

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bet initially would probably be to get

with some sort of an education company

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as a data analyst, so I was following.

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Ed tech, blogs of various kinds

and job postings through there,

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and I applied to a lot of jobs.

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Like I was more successful getting

interviews when I applied to jobs

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from some of these kind of less known.

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Venues.

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Um, I don't know if I ever really

got an interview from anything I

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applied for on LinkedIn, even if I

applied on the company website, but

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I'd found the listing on LinkedIn.

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I, you know, I just, I didn't

have the corporate background.

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I didn't have the connections, I didn't

have internal referrals, I had nothing.

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So I had to essentially called, call

everything and always sent cover

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letters that were very tailored.

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To the job.

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I always researched the company and I

probably applied to fewer places per week

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than many of the students in the program.

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But I only applied to jobs

that I thought I was really

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legitimately, pretty qual like that.

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I, there was a reason why

somebody might look at me even

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with my limited experience.

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Avery Smith: That makes a lot of sense.

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I think most people are on LinkedIn

and only looking at at LinkedIn jobs,

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which by the way, um, I don't know if

you have seen this, oh, you have seen

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this, but I have find data job.com

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now and premium data jobs, which are

trying to pull, help people find jobs that

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aren't necessarily listed on LinkedIn.

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So now you could have used those jobs

boards, but those didn't exist back then.

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You're applying to jobs you think

you're a good fit for, you're looking

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at job boards and job listings

that maybe other people aren't.

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And then.

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You're, you're trying to stand out because

you're sending, you're sending cover

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letters that are, that are quite tailored,

and then is that how, how you and

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Cynthia Clifford: following companies

that, that, that I, you know, ahead of

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time and commenting on, on that company's

posting and those things as well.

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Avery Smith: Okay.

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And how did you land your, your first job

with, uh, with Impossible, right, which is

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basically they make the, the vegan meat.

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Cynthia Clifford: I found that job on

tech Jobs for Good, and I wrote a really

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tailored cover letter because it was

very clear from the job description

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that cultural fit was really important.

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I made sure that they knew that I

tried impossible foods, that I, you

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know, made ccad with the impossible

beet for my vegetarian sons.

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That I really knew what I was, that,

that it's an important mission to

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try to reduce some of the greenhouse

gases from animal production and

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that I'm behind that mission, and I

think that's why I got an interview.

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Avery Smith: That's really cool that

you, you were really tying like,

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you're like, Hey, I'm not just another,

you're not just another company to me.

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I'm not just another candidate to you.

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I think this is a good culture fit.

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We should also mention that like you,

you live in Vermont, it's not like the

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biggest corporates tech hub of the United

States, so there's not a ton of data

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jobs in Vermont, so you are also looking

for remote, which, which obviously makes

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things, uh, a bit more, more competitive.

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Um, so you apply to this,

this job as a remote job.

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Do you remember what the

interview process was like at all?

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Cynthia Clifford: I had a screening with

the the, with the recruiter who passed

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me on to the hiring manager, and after I

met with her, I had four more interviews.

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With different people in either the

team or a team I might interact with.

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They were all half an hour.

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There were two back to back

and another two back to back.

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So I met altogether with, besides

the recruiter, with five people.

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And I do know that.

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They speeded the process up a little

bit because they asked me early on if I

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was close to an offer or I got an offer

from anybody else to let them know.

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And I did get an offer from, and now from,

uh, an agency in Vermont, a state agency.

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: 00:15:51

So I was able to sort of parlay that.

295

: 00:15:53

I mean, and it was legitimate.

296

: 00:15:55

I mean, I did get that offer, but.

297

: 00:15:56

It was, I was able to sort of put

pressure and move the process along.

298

: 00:16:00

Avery Smith: Okay.

299

: 00:16:01

And do you remember the

interview being hard?

300

: 00:16:03

Like were there difficult

technical questions?

301

: 00:16:05

Were they talking about stats or sequel?

302

: 00:16:08

Cynthia Clifford: No.

303

: 00:16:08

All really kind of cultural fit

and behavioral questions and I.

304

: 00:16:12

Avery Smith: I, I find a lot

of our students somehow get

305

: 00:16:16

internship or not internships.

306

: 00:16:17

I find a lot of our students get

interviews that are, are more behavioral

307

: 00:16:21

and, and less technical, which, which

I think is, is quite interesting.

308

: 00:16:25

Okay.

309

: 00:16:26

You're there for a bit.

310

: 00:16:27

And what type of tools, uh,

are you using on the job?

311

: 00:16:30

Cynthia Clifford: Mostly Google

Sheets slash Excel and creating

312

: 00:16:35

templates of various kinds so that

I could take data that I would,

313

: 00:16:38

would access from outside databases.

314

: 00:16:42

I could take it and plunk it in

and it would automatically update.

315

: 00:16:45

I had, I'd created a bunch

of these sort of tools.

316

: 00:16:48

I had to prepare the weekly sales

and share report, which went to

317

: 00:16:53

the executive leadership team.

318

: 00:16:55

That was all in PowerPoint, but I

would have to pull pictures out of

319

: 00:16:58

the, these templates that I had made.

320

: 00:17:01

So I used sheets, I used PowerPoint,

and, and then in the consumer

321

: 00:17:05

packaged goods industry, there

were a whole load of companies.

322

: 00:17:09

Numerator, IRI, Nielsen, MPD, they

all point of sales data, if you think

323

: 00:17:15

about it, is a massive data set.

324

: 00:17:17

And so they kind of aggregate all

of this and they have their own

325

: 00:17:22

proprietary systems and you companies

pay subscriptions to access this data.

326

: 00:17:27

And I would have to do the data pulls.

327

: 00:17:29

I really did pretty much all the

data pulls and supported the sales.

328

: 00:17:35

Team and created these reports and

the logic of these systems was quite

329

: 00:17:41

SQL based, but it wasn't SQL because

there was an, you know, an overlay.

330

: 00:17:46

But I would have to, you know,

pick this and group by this

331

: 00:17:50

and wasn't highly intuitive.

332

: 00:17:52

It was actually pretty hard to

learn some of these, and there were

333

: 00:17:55

like maybe three or four different

systems I had to learn and one was

334

: 00:18:00

for food service and one was for.

335

: 00:18:02

Something else and one was just for Kroger

and both was, and each was different.

336

: 00:18:08

Avery Smith: I think that's important

to to note because it's not like, like

337

: 00:18:12

in the accelerator that we can cover,

you know, this, these types of tools.

338

: 00:18:16

And honestly like most jobs have some

sort of proprietary data software or

339

: 00:18:21

industry specific data software that like.

340

: 00:18:24

Really you don't even know

exists until you're there.

341

: 00:18:27

And even if you did know exists, you

probably really couldn't access it, uh,

342

: 00:18:30

unless you work for like a corporation.

343

: 00:18:32

So it's, it's like that's

exists at every job I

344

: 00:18:34

Cynthia Clifford: was interviewing.

345

: 00:18:35

They told me that I, part of the

job I would have to access IRI data.

346

: 00:18:40

So I looked up that thinking,

all right, well, I'll go see

347

: 00:18:43

what this is like before.

348

: 00:18:45

And to be even to get, be even

a researcher and get access

349

: 00:18:49

was over a thousand dollars.

350

: 00:18:51

So I was like, well, I guess

I'm not gonna access that.

351

: 00:18:54

Avery Smith: That's, that's how that goes.

352

: 00:18:56

Uh, that makes a lot of sense.

353

: 00:18:57

And you're wise for like, trying to look

it up beforehand and, and be prepared.

354

: 00:19:01

That was, that's really cool.

355

: 00:19:02

Okay, pause for a second.

356

: 00:19:04

Uh, I didn't really think through how

we wanna transition to your second job.

357

: 00:19:09

Uh.

358

: 00:19:10

I can say you're just there for a while

and then like you ended up getting

359

: 00:19:13

into, and they had had a reduction in

360

: 00:19:15

Cynthia Clifford: force and they moved.

361

: 00:19:16

Um, and well that what, what they

actually did was they reclassified

362

: 00:19:20

all these jobs as hybrid honest truth.

363

: 00:19:23

They did that because they

wanted people to quit, but Yes.

364

: 00:19:26

Um, because they had then ended up

with a big layoff shortly after that.

365

: 00:19:29

So I think we can just sort

of say there was sort of.

366

: 00:19:33

They, they transitioned jobs and

there was a reduction in force.

367

: 00:19:37

Avery Smith: Okay, so you're at

Impossible Foods for a while.

368

: 00:19:39

And then they ended up kind of

reclassifying a lot of jobs to, instead

369

: 00:19:43

of being remotes, to be hybrid and, uh,

their, their offices are not in Vermont.

370

: 00:19:47

And so you ended up, uh, not being

able to work at them and any further.

371

: 00:19:52

And then you had to

find, uh, a new data job.

372

: 00:19:55

How did you find the second data job?

373

: 00:19:57

Cynthia Clifford: Well, I actually,

this time I had several internal

374

: 00:19:59

referrals for things within the

consumer packaged goods industry.

375

: 00:20:02

So I was pursuing those.

376

: 00:20:04

I also was pursuing things I'd

found on LinkedIn or on your

377

: 00:20:07

job boards or, and I gone.

378

: 00:20:10

Actually the final round four

times and didn't get the job.

379

: 00:20:15

It was exhausting.

380

: 00:20:16

I mean, you know, done the project,

done a panel presentation, like

381

: 00:20:20

all sorts of stuff for several

jobs and was feeling pretty down.

382

: 00:20:25

And I'm not, and somebody I know

from LinkedIn and I think from this

383

: 00:20:30

program, but, uh, okay, so someone

from the program who I'd connected

384

: 00:20:34

with and we've had coffee chats with.

385

: 00:20:37

And continued to keep in contact

with, 'cause I always appreciate

386

: 00:20:40

her thoughtful comments on LinkedIn.

387

: 00:20:43

I had chatted with her, uh, because

she was looking for a new, a new role

388

: 00:20:48

or had just gone through the process

of looking for a new role and I let

389

: 00:20:52

her know with the position I was in,

and she actually said to me, I just

390

: 00:20:56

interviewed with a company and I.

391

: 00:21:00

They offered me a job

and I'm not taking it.

392

: 00:21:03

And she said, not because it wasn't

a good job or a good company,

393

: 00:21:07

but she had personal reasons for

why it wasn't the best fit for

394

: 00:21:11

her circumstances at the time.

395

: 00:21:13

And she said, if you'd like,

I'll, I'll write to the hiring

396

: 00:21:17

manager and recommend you.

397

: 00:21:20

So even though she had turned this job

down, she wrote to the hiring manager

398

: 00:21:24

and or to the, the recruiter and told

him that she thought I would be a

399

: 00:21:29

great fit and I ended up meeting with

him without actually even applying.

400

: 00:21:34

And he then set me up to interview with

the hiring managers also before I'd ever

401

: 00:21:40

filled out an application on the site.

402

: 00:21:43

And.

403

: 00:21:44

Because I know that after, after

meeting with the hiring managers, the

404

: 00:21:48

recruiters said, you know, we need to

have you fill out this application.

405

: 00:21:51

And she was great because she had

given me a little bit of heads up

406

: 00:21:54

about the sorts of questions they were

gonna ask me in the interview as well.

407

: 00:21:58

So I was able to be very prepared.

408

: 00:22:00

The interview was.

409

: 00:22:02

With the hiring managers.

410

: 00:22:03

There were two of them.

411

: 00:22:04

It was a, it was a good interview.

412

: 00:22:05

They were both really thoughtful.

413

: 00:22:07

It was clear that they

had a set of questions.

414

: 00:22:10

They were growing the team substantially.

415

: 00:22:12

A, a year before I joined, this

particular team had maybe five or six,

416

: 00:22:16

maybe seven people, and now we're 20

and they'd hired, I was one of the

417

: 00:22:20

last of this big explosion of hires.

418

: 00:22:24

The.

419

: 00:22:24

Questions were a mix of, I wouldn't say

highly technical, but they did ask what

420

: 00:22:29

I, I mean, this is in the energy industry.

421

: 00:22:32

They asked, you know, what I knew

about how power was generated.

422

: 00:22:35

They asked if.

423

: 00:22:37

They asked questions about what was

the most complex sorts of things

424

: 00:22:40

I've ever done with Excel, but they

also asked behavioral questions.

425

: 00:22:44

Avery Smith: Well, what's cool is,

you know, you have been working as an

426

: 00:22:47

international teacher for, for a while,

but you studied engineering in school

427

: 00:22:51

and you even had an engineering job, you

know, out of college for a little bit.

428

: 00:22:55

So I'm sure that like not only having

this awesome, basically internal

429

: 00:23:00

reference to the hiring manager.

430

: 00:23:02

Also being like, Hey, look, I

understand engineering principles.

431

: 00:23:06

I think that probably sets you

apart compared to most analysts.

432

: 00:23:09

Cynthia Clifford: Oh, for sure.

433

: 00:23:10

Because when they asked me, you know, what

I knew about how energy was generated,

434

: 00:23:15

you know, you know, I was like, well, I.

435

: 00:23:17

I just spew off an answer like, well,

there's lots and lots of ways of, you

436

: 00:23:21

know, getting, you know, converting

sort of potential energy to kinetic

437

: 00:23:25

energy and getting that turbine moving

and getting, you know, and like I, you

438

: 00:23:29

know, I went on and thought it on, I

think, and, and it's been really useful

439

: 00:23:34

in my work there to have that sort

of understanding all of the analysts.

440

: 00:23:39

Take Workday courses all on

things like HVAC systems and,

441

: 00:23:44

and when I was an engineer, you

were chemical, I was mechanical

442

: 00:23:48

and thermodynamics was actually.

443

: 00:23:50

My best subject engineering job

I had when I was an engineer

444

: 00:23:55

was in energy conservation.

445

: 00:23:57

So even though it was quite a

while ago, those fundamentals are

446

: 00:24:01

in there and it's helpful now.

447

: 00:24:03

Avery Smith: Very cool.

448

: 00:24:04

I wanted, I wanted to ask earlier, like,

you know, even though you were a teacher.

449

: 00:24:08

Did you find that you had transfer

transferable skills into analytics,

450

: 00:24:12

and obviously sounds like in this

case your, your engineering background

451

: 00:24:15

stuff was, was transferable.

452

: 00:24:17

Were some of your teacher

skills transferable as well?

453

: 00:24:20

Cynthia Clifford: Oh, for sure.

454

: 00:24:21

I think that, I mean,

in a variety of ways.

455

: 00:24:24

In my current role we are,

we do a lot with statistics.

456

: 00:24:28

We look at the statistics of models,

are these appropriate models?

457

: 00:24:32

Are is the, are the residuals

normally distributed?

458

: 00:24:35

That sort of thing.

459

: 00:24:36

And having taught higher level math

and AP statistics, I've been able

460

: 00:24:42

to actually contribute to my team.

461

: 00:24:45

By creating, we have team weekly

team meetings that are team trainings

462

: 00:24:49

where people will present things and

I presented on, oh, here's the Durbin

463

: 00:24:54

Watson statistic and auto correlation,

and what does it really mean?

464

: 00:24:57

And used really simple examples that.

465

: 00:25:00

That aren't necessarily embedded in

the energy context, but are maybe

466

: 00:25:04

embedded in ice cream shops and beaches.

467

: 00:25:07

Everybody can understand and people have

said that they've been really helpful.

468

: 00:25:10

I, knowing the statistics has certainly

been transferable and, and, and math

469

: 00:25:16

modeling, I mean, understanding variables.

470

: 00:25:18

I, you know, I was the calculus

lady, but other skills that all

471

: 00:25:22

teachers have are really transferable.

472

: 00:25:25

Teachers can learn new things.

473

: 00:25:27

When you're a teacher, you.

474

: 00:25:29

You get thrown into, you know, they'll

be like, oh, we have a new software that

475

: 00:25:33

we're gonna use for, you know, great.

476

: 00:25:35

And they'll bring one person in and

do a two hour point and click and

477

: 00:25:38

then they'll be like, off you go.

478

: 00:25:40

And teachers figure it out.

479

: 00:25:42

'cause they have to, I've been surprised

in the corporate world actually,

480

: 00:25:46

how much time they give you to.

481

: 00:25:48

Learn things.

482

: 00:25:50

'cause when you're a teacher,

they don't give you that.

483

: 00:25:52

I think things like knowing how to

do a presentation in, in Impossible

484

: 00:25:56

Foods, I had to make PowerPoints.

485

: 00:25:57

Like I actually, at one point, I, I

looked at the PowerPoint and I was like,

486

: 00:26:03

you know, we just come out with these

new company color branding and like,

487

: 00:26:06

is is there any chance I could like

redo the template for the PowerPoint?

488

: 00:26:11

So it's very cohesive, like, and what I

made then ended up saw it showing up in.

489

: 00:26:19

People much higher than me kind of taking

my templates and using them because

490

: 00:26:24

I, I know how to make a power one.

491

: 00:26:26

Avery Smith: There's, there's all

sorts of different ways that teachers

492

: 00:26:29

can, you know, transferable skills.

493

: 00:26:31

Even, even when you said earlier when

you were talking about some of the

494

: 00:26:33

statistics and, you know, maybe not in

energy, but like in ice groups and stuff

495

: 00:26:36

like that, teachers are, are good at

explaining things and really like what

496

: 00:26:41

you're actually doing as a data analyst.

497

: 00:26:44

A lot of the time is just telling business

people or higher ups what's happening in

498

: 00:26:50

the business from a numbers perspective.

499

: 00:26:51

And so as a teacher, you're, you're,

you've been trained to communicate

500

: 00:26:55

clearly, whether it's in a PowerPoint

or, or orally to say what's going on.

501

: 00:26:59

Uh, and like you said, also,

teachers are fantastic students.

502

: 00:27:02

And like you said, at Impossible Foods,

you had to learn this like proprietary

503

: 00:27:06

database system that like you couldn't

really learn on your own beforehand.

504

: 00:27:10

At your, your current company.

505

: 00:27:12

We haven't talked about it, but

you use this software called jump.

506

: 00:27:15

JMPI really like jump as well,

but it's not like something that's

507

: 00:27:19

really, it's not super common.

508

: 00:27:21

It's, it's an awesome tool, but it's not

super common and it's quite expensive.

509

: 00:27:24

Um, if you try to get like a

license on your own, it's gonna

510

: 00:27:27

cost you about $2,000 a year.

511

: 00:27:28

So it's not like something you, no

one really learns, jump on their

512

: 00:27:31

own and then gets into a job.

513

: 00:27:32

You always learn jump.

514

: 00:27:33

On the job, and that's something

that teachers are gonna excel at.

515

: 00:27:36

They're gonna be great.

516

: 00:27:37

And, uh, to be honest, especially with

how AI's going right now, like we're

517

: 00:27:41

gonna have to keep learning new things

year after year after year as a data

518

: 00:27:44

analyst for the next two or three decades.

519

: 00:27:47

Cynthia Clifford: Well, I use AI

a lot of times in, in my role when

520

: 00:27:50

I'm, I'm doing some of the Excel

based work and I know I wanna maybe.

521

: 00:27:55

Pull something from this tab over to this

one and, and aggregate it by the week.

522

: 00:28:01

And, but when I, if I have blanks, I

don't want them to show up as zeros.

523

: 00:28:06

I want them to show up as nas, then I will

put the appropriate information, describe

524

: 00:28:13

the situation and put that into ai.

525

: 00:28:15

'cause you, you can't obviously,

you know, company spreadsheet, you

526

: 00:28:20

know, with chat GPT, but, but I will

put in the relevant information and.

527

: 00:28:25

I ask for the, the code, and it's really

good at giving me very succinct ways

528

: 00:28:31

to do some of the things I need to do.

529

: 00:28:33

Avery Smith: I, I love that.

530

: 00:28:34

It's just AI is not replacing us.

531

: 00:28:36

It's just helping us work faster.

532

: 00:28:38

Um, I think that's really cool.

533

: 00:28:40

Has anything, has anything really

surprised you as a data analyst?

534

: 00:28:43

Like maybe something you didn't realize

that, that the job would be like?

535

: 00:28:46

I.

536

: 00:28:47

Cynthia Clifford: Well, I would say

that my first role, I was surprised by

537

: 00:28:52

a lot of things, but a lot of that was

more just the way that corporate works.

538

: 00:28:56

Coming from a teaching background, I,

things are so different in teaching.

539

: 00:29:02

They want you to get something done

fast and it might not be the most

540

: 00:29:06

perfect version of something, but

if they say they want this, they,

541

: 00:29:10

well, they'll get something and

they'll get it when they need it.

542

: 00:29:14

I found that I had that

mentality and would be like,

543

: 00:29:19

well, did you proofread this?

544

: 00:29:21

Did you, I mean, like of course I

proofread it, but did you check this?

545

: 00:29:25

Did you run it by three or four

other people and get their feedback?

546

: 00:29:27

Did you do like for things that

were supposed to be rushed and.

547

: 00:29:32

Could end up being, we're gonna

roll this new dashboard out,

548

: 00:29:36

it's gonna take two months.

549

: 00:29:38

And teaching it would be like, well,

here it is, and like, you know, start

550

: 00:29:42

playing with it and figure out what

you can, if there's problems, let me

551

: 00:29:45

know if there's problems, let me know.

552

: 00:29:48

Be an issue.

553

: 00:29:48

In teaching, it would be part of

the process of how things work.

554

: 00:29:52

And it seems like in the corporate

world, it's all a lot slower.

555

: 00:29:57

But it has to be right.

556

: 00:29:58

Like they're not iterating

constantly on the fly.

557

: 00:30:02

You're supposed to do all these

iterations and then say, here,

558

: 00:30:06

Avery Smith: it's, it's, it's definitely

a different world than, than teaching.

559

: 00:30:09

Uh, for sure.

560

: 00:30:10

What advice would you give to teachers

who want to become data analysts?

561

: 00:30:14

Cynthia Clifford: The teachers are

constantly evaluating and, and assessing

562

: 00:30:19

the situation and our problem solving

and data analysis really is about problem

563

: 00:30:24

solving and communicating the results

of the problems you've solved or, you

564

: 00:30:29

know, every, like you said before,

if, if, if they're sales data you're

565

: 00:30:33

trying to explain to an executive, not,

you don't need to explain that the.

566

: 00:30:38

Sales went up, or sales went down.

567

: 00:30:40

That's a, like a concrete number,

but you're trying to dig into

568

: 00:30:44

why and what other drivers are

there that made that happen?

569

: 00:30:48

Or in my current role, which are the

variables that are gonna best explain,

570

: 00:30:54

uh, best represent, allow us to create

a model that will describe a company's.

571

: 00:31:01

And there might be tons of different

variables, but we're trying to

572

: 00:31:04

come up with the ones like a really

simple model that will still explain

573

: 00:31:08

really clearly and teachers do the

same thought process all the time.

574

: 00:31:14

Why is Joey not understanding?

575

: 00:31:16

This concept?

576

: 00:31:17

What is going on?

577

: 00:31:18

Is there a piece that's missing?

578

: 00:31:20

Is there like all that back

thinking and the, Hmm, let me think.

579

: 00:31:24

Let me take a look.

580

: 00:31:24

Does he know how to do this?

581

: 00:31:25

Does he know how to do this?

582

: 00:31:26

Does he know how to do this?

583

: 00:31:27

Oh, and then he doesn't

know how to do that.

584

: 00:31:29

So somewhere there's this connection that

Joey's not making or Johnny's not making.

585

: 00:31:33

Teachers do that all the time, and

they do it for rooms full of kids.

586

: 00:31:37

And they finish the day and they ruminate

over what went well and what didn't

587

: 00:31:43

go well and why you're just applying

that same skillset, that same sort

588

: 00:31:48

of thought process to a new context.

589

: 00:31:52

Avery Smith: It's problem solving at

the end of the day, and teachers have

590

: 00:31:54

always been good problem solvers.

591

: 00:31:56

Uh, Cindy, you're one of the

best problem solvers I know.

592

: 00:32:00

Uh, and I'm sure, uh, your current

company is super lucky to have

593

: 00:32:04

you, and I was lucky to have you.

594

: 00:32:05

As a student in, in the Accelerator.

595

: 00:32:07

Thanks so much for coming on the

show and, uh, sharing your story.

596

: 00:32:11

Cynthia Clifford: No, it was my pleasure.

597

: 00:32:12

It was really good to catch up.

598

: 00:32:13

Avery, you were wonderful

to me and continue to be

599

: 00:32:16

Avery Smith: good.

600

: 00:32:16

I'm glad I.