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Teacher to Data Scientist
22 Plays8 months ago
Timothy is a data scientist at the NYC Department of Transportation analyzing CitiBike ridership data.
He shares unconventional job hunting tips and highlights the necessity of continuous learning in the ever-evolving field of data science.
Questions for Timothy or the host? Email us at [email protected]
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Transcript
Springboard's RISE Conference Discussion
00:00:14
Speaker
Hello, everyone. I hope this episode of the podcast finds you well. I know a lot of people this past weekend attended Springboard's annual RISE conference. I personally was unable to attend as I was traveling to North Carolina, but I followed along on Instagram. All of the keynote speakers from companies like Google, IDO, they sounded incredible. A little bit of FOMO there on my end.
00:00:40
Speaker
I was super excited to see the alumni on the success stories. I'll be speaking with some of them more on this podcast. So if you were like me and could not go, I will be bringing them here to this platform.
Introducing Timothy
00:00:52
Speaker
I also saw that there was a topic on
00:00:55
Speaker
If AI will be taking over UX, I certainly have opinions on that, but I'll save them for a more applicable time because today you're kicking off this podcast with what Abby and I promised, a story from a different alum each episode. And today I'm so excited to have you meet Timothy.
Timothy's Academic Journey to Data Science
00:01:15
Speaker
Timothy is a data scientist at the New York City Department of Transportation. He completed the Springboard Data Science Program in 2022.
00:01:23
Speaker
and now works on the data projects analyzing city bike ridership data. He also spent time as an analyst with Caesars Entertainment, where he worked in the Enterprise Data Warehouse department, supporting various analytical teams and their data pipelines. Welcome, Timothy. How are you today? I'm good. Thank you for having me here. I'm excited to be part of the podcast.
00:01:49
Speaker
Likewise, and when I saw that you worked for the New York City Department of Transportation, I as a New Yorker myself, I had some notes for you. I remember one of the first assignments Springboard assigned the UX students was to go to a location and observe people using something.
00:02:09
Speaker
So I sat in the subway and watched people use a broken ticket machine. And it was just mayhem, but you work for Citi Bike. So we'll just have to talk about how you got to where you are instead of just hearing me complain about the subway.
00:02:25
Speaker
As a shameless plug, I will say that a city bike is an excellent alternative to the bus transit system if you're in New York City. But I think a lot of people tend to use it for the first mile of the travel and the last mile of the travel, and that's a great thing.
Transitioning Careers During the Pandemic
00:02:41
Speaker
Yeah, I'm excited to talk about my journey, if you had any specific questions about it, or if we're just going to give an overview.
00:02:48
Speaker
Well, yeah, I'd love to hear where you were before you even decided to get into data analytics. What were you doing in the before times? The dark before times before all of that data. Before you worked for the New York City Department of Transportation, which is clearly the best.
00:03:09
Speaker
Yeah, so I was actually in academia. I went to a little university called the University of Southern California, where I studied neuroscience and got a master's degree in neuroimaging and informatics. So for a lot of my life, you know, I was really interested in brains. And so I ended up learning about brains in college.
00:03:31
Speaker
And I think the great thing about the neuroscience track and the neuroimaging track that I took was the fact that it is all kind of founded on data. So I think my journey in data really started very early on.
Challenges in Job Hunting
00:03:42
Speaker
It just wasn't so apparent at the time. I think when I was going to school that the title data scientist wasn't really as prominent as it is now. And so it didn't really occur to me that that was a path to take.
00:03:57
Speaker
And so that's why I started teaching after I finished my master's degree. I went to teach, you know, in the UC university at USC. And this was after I had did a brief stint in Alaska as an image specialist. So kind of a precursor to image and notification kind of that we see now with the computer vision, right? Kind of some sort of rudimentary techniques were used to analyze images. Um, much like how we have TensorFlow now.
00:04:27
Speaker
So I've always been interested in data. It wasn't until really the pandemic hit where when my instructional contract was greatly threatened by the changing times, I sat down with
00:04:44
Speaker
with my partner, my now wife. And she was like, why don't you just crunch numbers for the thing? You know, do data. You know, you're smart. You like numbers. And I was like, sure, I'll look into it. And really, it kind of hit this perfect combination of programming and statistical analysis, which really reminded me of what I was doing in Masters.
00:05:06
Speaker
in my master's program, you know, taking brain images, writing programs to analyze them. So I think it really felt like a very natural transition for me to kind of go back to that realm of data, you know, and I did the streamboard bootcamp, you know, worked my butt off for like three months, interviewed for quite a few, quite a
Interview Experiences at Caesars Entertainment
00:05:27
Speaker
bit longer than that. And then I did my first job at CCS entertainments, working with the enterprise data warehouse team,
00:05:34
Speaker
And now I'm here in New York City, looking for the Department of Transportation as a data scientist. That's fascinating in the sense that data has always been a part of your life. And I don't know enough about the data science field, but I guess back when you were exploring that space, for lack of other words, data science wasn't a profession yet. Is that accurate?
00:06:02
Speaker
I definitely think it was a profession. I just wasn't fully aware of it. And it definitely was not at the same scale that it is now. I think it's definitely evolved in the past decade. Like it really came to the forefront in the past decade because these companies were collecting so much data that they needed somebody who was specialized in the, you know,
00:06:26
Speaker
and the analysis of it.
Current Projects at NYC Department of Transportation
00:06:28
Speaker
And so I think it was a natural kind of progression from your traditional data analytics. And with more advanced machine learning techniques coming out, with more advanced kind of computational designs, it became a very natural pathway. And so it kind of grew and became much more popular as these kind of technologies and computational skills started to be more frequent.
00:06:56
Speaker
Certainly, I can't think of any, I know data is way more than this, but I can't think of any website product that I use online where I don't have to enter my name, email, telephone number. Obviously, again, there's more data to be collected on a person. But yeah, I can't even imagine the amount of data that is being collected by these companies.
Impact of Public Service Role
00:07:21
Speaker
So
00:07:23
Speaker
I'd love to hear a little bit more about how you ended up at Springboard. Obviously, you had this conversation with your wife. She thinks you're smart. And what made you look into data science as more of a serious profession? How did you find Springboard? I wanted the first part, which is why data science?
00:07:47
Speaker
I think at first I was really thinking data analytics because in my mind, data analytics would lead to data science. And so I was like, well, let me start with analytics because at the time my technical skills technically weren't very strong, right? I did dabble in code, but not to the extent where I thought I could really comfortably be a data scientist.
00:08:12
Speaker
And so really I started looking into the analytics programs, right? I like math, which is very weird to say, I think, but I like math. You know, I took advanced calculus in college. I enjoy statistical methods. I like learning and reading about like weird mathematical formulae. And so I think that analytics felt very natural because I was used to dealing with epigenetics data, you know, the brain genome, which is like,
00:08:41
Speaker
gigabytes, gigabytes of data per person. And, you know, and so I was looking at data analytics first, but then I found
Future Growth and Career Advice
00:08:48
Speaker
out about data science and it seemed like a great challenge. And so how I ended up at Springboard was actually through a lot of research. I looked up a lot of programs, looked up kind of all the different bootcamps out there. I did a lot of cost analysis of like what is offered, what is an offer.
00:09:10
Speaker
And Springboard at the time felt like the best in terms of breadth of what they covered and it seemed quite thorough. And so I went for the Springboard data and actually signed up first for the data analytics program, but they accidentally sent me the data scientists, I guess, pre-exam. And they said, I did well enough that I should consider doing data science.
00:09:38
Speaker
Oh, interesting. So you have to test into this data science program. Yeah, for both, I know, actually for both data analytics and data science, there's like a pre-exam data have you take just kind of to test your
00:09:53
Speaker
rudimentary foundational skills. I see. Oh, I didn't know that. The more you know. That's great. So I love how that was kind of a happy coincidence that they suggested something else for you. So you're enrolled now. Tell me a little bit about your experience in the program. What did you find useful within it that maybe set you up for where you are today?
00:10:17
Speaker
Yeah. So I think that for the most part, the program was decently structured. There was definitely a concrete path to follow. And I think that helped a lot when you're someone who is new to the, to the field and making a complete transition, right? It can be quite daunting and just plenty of resources out there. Just plenty of online resources out there, but really it's how do you combine those resources together into a meaningful path?
00:10:43
Speaker
And I think without knowing a lot about the industry, that's quite challenging. So I would say that was kind of the major benefit of Springboard is not necessarily that there were extremely unique or or inaccessible otherwise resources, right? The resources are all out there. It was just that they put it together for you in a package that made it a bit more accessible.
00:11:08
Speaker
I think that's a great way to put it. I personally, when looking into UX careers, there are some self-taught UX designers. They never did any formal, informal education. They just taught themselves. And I knew I couldn't do that. And to your point, yeah, not knowing anything about the industry, putting those pieces together would be incredibly challenging.
00:11:33
Speaker
So with that being said, was there anything outside of the course that you did that helped prepare you a little bit? I'll be honest, I did quite a lot outside of the course. I found that the material provided by Springboard was a great introduction, but not quite at the depth of understanding that I desired. And I felt that in order to truly feel like I was ready, I had to do a lot of outside research. And so I would say 50% of my time spent
00:12:02
Speaker
on the bootcamp, 50% was spent on doing external readings. And so I did things like I bought books, you know, I read a lot of books about data science, about machine learning, about very specific topics of machine learning that I was interested in. I did online courses through other websites like Udemy and Coursera, where I was able to sit down and follow another course on like fundamental Python and mathematics for data science. And so I think that as, as
00:12:32
Speaker
nice it was to have that material laid out for you in springboard, you know, it's designed so that you could finish it in a kind of fixed period of time. And maybe this was from my experience in academia, I knew that the depth wasn't quite there for me.
00:12:52
Speaker
And so I wanted more information as I sought out that information. So yeah, I did a lot of reading and a lot of watching videos and practice. Great. Was there anything specific within those videos, like any topics that really stuck out to you that you felt you needed to know? There was nothing technical. I don't think that technical skill is necessarily something that
00:13:22
Speaker
is so inaccessible or mysterious, right? It's really just about spending time learning. And so I think what really stuck out to me in the videos, they didn't say it the exact way, so I'm going to say it a little bit more bluntly. And actually, it's a paper, not a paper, it was a, I guess, an article that was submitted to a science research journal. And I actually shared this with a friend recently. It's the importance of stupidity.
00:13:52
Speaker
And when I say that the most important thing you'll have to learn is not any technical skill because you could learn any technical skill, but rather the acceptance of being kind of stupid. Sometimes you have to acknowledge that, you know, you will start knowing next to nothing and then you'll spend years on something and then you'll know a little bit more than nothing.
00:14:18
Speaker
especially in a field like data science and technology where things move so quickly and things change so quickly, accepting that you'll kind of have a sense of being behind is a big part of the career. And I think that is kind of what motivated me because one, I'm stubborn and I don't like to be stupid. And two, accepting that it's normal to feel this way,
00:14:43
Speaker
really motivated me, really prevented me from being scared of trying out new things. Yeah, I think that's so important to bring up in the sense of a lot of people probably are in careers where they're expected to know everything and perform. And it is very scary in that situation where you just don't
00:15:09
Speaker
know everything. I know in UX you're supposed to stay very objective and it took me a little bit to actually be comfortable asking dumb questions to figure out what I needed to do.
00:15:23
Speaker
So definitely amazing insight there. So now that, you know, you're finishing the course, I'd love to hear a little bit more about your job hunt because that's the most intimidating thing post bootcamp in my opinion. I don't know if this was the most intimidating thing for you, but what was that like?
00:15:43
Speaker
Uh, in one word, terrible. Okay. She's elaborate. Use as many words as you like. It's rough. And it's, it's rough. And I'm going to sugarcoat it. You have to kind of be ready to, like as hard as it was to learn, it's, it's much harder to have to prove that, you know, things a bit more concretely. You know, I think I got.
00:16:10
Speaker
pretty lucky. It took me about six months to find a new position. I already had a job, so I wasn't super in dire straits if I didn't find a job. But I was trying to get out of my position. And so it took me about six months, a lot of rejection. I applied to a bunch of jobs. Some jobs ended up not even responding. We all know that. Some jobs rejected me.
00:16:36
Speaker
Sometimes you would get a call from a recruiter, you would answer, you would get them all these things and they're like, oh yeah, yeah, yeah, we'll let you know, we'll let you know and you'll hear nothing. Um, I made it to the final stages on a couple occasions and then it turned out that they're no longer hiring for the position because of shifting needs, shifting finances. So just like understand that on some level, yes, you have to prepare yourself. You have to practice, you have to know what you're talking about. You're going to have,
00:17:06
Speaker
Do you have to have confidence? But accept that it's not all you. There are factors outside of your control that are preventing you from getting hired as well.
00:17:18
Speaker
That's absolutely true. Even when I worked in my other professions, I would try to hire interns and HR just would not even participate with my needs. So even though I wanted to hire people, yes, that's absolutely very true.
00:17:38
Speaker
I don't think anyone's ever said, wow, that job hunting experience was incredible. So you're not alone. And, but it still sucks to hear that it was tough. Do you have a number of how many jobs you apply for? Oh, ballpark, probably some quick math. I applied to like five to 10 a day for like pretty much every day. We're like couple hundred to 300 or more.
00:18:07
Speaker
You know, and obviously some of them are quick, right? Some of them we use kind of like quick apply, quick apply, quick apply. But yeah, it was quite a large number. I want to say about 200 to 300 jobs.
00:18:18
Speaker
which is not as much as some people have. I mean, I heard some people apply to thousands of jobs and still struggle. So I couldn't imagine. Yeah. I don't think I quite applied for that many. However, going back to like you were having interviews, you were getting to third round. So that clearly meant you were doing something right. Yeah. I'm going to give advice that no or very few career people are going to give you, but only people who've gotten the job were going to give you.
00:18:47
Speaker
This is coming from a, I think, I think anybody who's in the career guidance role is going, not going to say this, but I think the best advice you can have is fake it till you make it. And what I mean is be confident in yourself. I think my first few interviews were tough because I was a little like unsure. I was kind of like underselling a little bit or, you know, I was, I was.
00:19:15
Speaker
not being as descriptive as it could be. I know I'm not saying to flat out lie, but you should definitely give yourself the best opportunity and make yourself look as good as you can. I had a very interesting journey, I suppose, when I was applying. And so that's why I say fake it till you make it. I completely agree with that. And I have,
00:19:44
Speaker
I also do agree. I think a real career coach would not push for embellishing things. Or maybe my analogy would be to make your career story insta-worthy in a way, you know? Yeah, you do kind of have to.
00:20:05
Speaker
Maybe BS a little bit, but don't lie, for sure. For sure. You use years on your resume, you don't use months. Make it years. That kind of... We round one month up to one year now. Absolutely. I worked there for three months, three years and a month. That's four years now. Well, I mean, do you know people will conduct background checks?
00:20:32
Speaker
They do verify, they trust the verify. And I will say, I think a good analogy is, is if you're trying to sell something like a used item, would you understate how great it was? Or would you be like, would you just kind of say, yeah, it's it's all right. You know, it's got some use, but.
00:20:55
Speaker
You know, you probably like it. Or would you say like, yeah, this is like the best thing I've ever used. Then I got a lot of use of it. It was such an amazing product. And you have to think about yourself in the same way that you are trying to sell yourself to this person who does not know you. They're not going to make the best assumption about you. They're only going to take your word for things. And if you don't give them your word, well, they're not going to give your word to the person who's making the decisions. I think that's a great way to put it. If you can't display
00:21:24
Speaker
that confidence of what you're doing to convince the hiring manager, absolutely. That very much rang true when I interviewed at Verizon. I knew within the job description, I had done all of those things within springboard, within my internship that springboard placed me in, that I felt confident enough in doing that at Verizon.
00:21:50
Speaker
Yeah, you just have to go for it. But I definitely did look at certain jobs where I felt I was not qualified for. There are some boundaries I had. I'm sure, Timothy, you did have where you were like, this job is not for me. Apply to anything and everything your heart is set on. No, I think that
00:22:11
Speaker
Actually, let me share a very funny story. This is how little I knew about the tech job world. So in the tech world, there's a position level called staff. And anybody who's in tech knows about what that means.
00:22:26
Speaker
As a person who wasn't in tech, I was like, Oh, staff, you're just like a staff member. You're just like a person. So I applied to it. And I was like, and then I look at the experience. I was like, Oh, like media, like middle experience, right? Three ish to some level years. I was like, ah, I'll apply. Um, instantly rejected. And I was like, Hey.
00:22:49
Speaker
I asked a friend, I was like, Hey, what, why did I get it? It rejected so fast from this like position. And they're like, well, it's a staff position. I was like, yeah, but what is it? Is that's not entry level? And they're like, no, uh, apparently staff is medium to upper level of, um,
00:23:11
Speaker
I guess the position that you're in, you know, it's quite high. It's definitely not entry level. It's a little bit like upper mid level. And I was like, Oh, well, that makes sense. But the reason why apply wasn't necessarily just the title, but it was more so that, you know, the experience and the questions they were asking, I felt like, well, I could do that. You know, and, and realistically, you have to look at positions, not just in the title or.
00:23:40
Speaker
They just don't look at not just the title, but look at what they're asking for and decide for yourself, can I do this? Is this something I can do? I think I could do it. Can I convince somebody else I can do it? I think so. And then just apply. Now, if they're asking for five to seven years in data science and four to six years in B2C, very specific things that you definitely don't have the experience in.
00:24:05
Speaker
Maybe don't apply, but if it's like two to three years or one to three years and they're like, Hey, Python experienced two plus years. I think that's still worth throwing your hat in the ring because sometimes they ask for things that they don't really know.
00:24:22
Speaker
how much they want, or they're much more willing to train than they want to put on paper. And so again, kind of circling back to the fake it till you make it mantra, decide whether or not... And again, if it's a dream company of yours, if it's a dream field of yours, and something you have a lot of... Again, I think something to also consider is experience in the field.
00:24:48
Speaker
Have you been working in this industry for a long time? You just wanted to be a data scientist. I would say even if your technical skills aren't quite there, you know, apply. I think that most people would agree that domain knowledge and industry experience kind of outweighs raw technical talent most of the time, as long as you have a reasonable amount, again, reasonable amount of technical skill.
00:25:13
Speaker
Right. Obviously I'm not a data science expert, but using Python, I've never used Python. I just know that it exists. So that would make no sense for me to apply to a job and expect them to teach me Python. I think that advice is very spot on. And I would love to kind of hear about
00:25:35
Speaker
your interview process with Caesars because that was your first job out of bootcamp. Let me back up. Tell me how this interview process went. Well, it was a fun one, as you know. I thought you said it was terrible. Well, I like adventures. It was fun in that sense.
00:25:56
Speaker
It was kind of miserable and looking back on it, it's one of those like, Oh, this is hilarious. Uh, in the moment it was kind of terrible. So I had applied for Caesars back way, way back. I think it must've been like October or November. And I landed interview.
00:26:17
Speaker
And I speak with somebody quite high up, actually. And for those of you who don't know, typically, you don't speak to higher up managers until the later stages of the interview. Normally, the first stages are lower middle management. Anyway, so I talked to this person. I applied for a data analytics position at Caesars because it was kind of adjacent to my data science skills.
00:26:44
Speaker
And I landed an interview and I did this interview. And at the end of the interview, the person's person was quite honest. They were like, well.
00:26:57
Speaker
you might be overqualified given your technical ability. And I was like, Oh no, no, I'm not. No, I'm not. I didn't say that. I was like, no, wait, hold on. Wait, wait, wait. You definitely felt that. And then they were like, well, you know, this person in another department might be, might be interested in you and this is their name and so on and so forth. And I was like, Oh, okay, cool. Like thank you. And you know, that was that.
00:27:24
Speaker
hear nothing for like, you know, I send a follow up by the way, always in a follow-up email. I send a follow-up email. I was like, Hey, just to touch with so-and-so with the like coordinator person. And they were like, yeah, well, we'll be in touch. And I was like, okay, great. Hear nothing for like a month and a half. It can literally radio silence. I was like, I guess that's done. Get a random email saying, Hey, this is so-and-so from Caesars. We want like to interview you for a data scientist position.
00:27:55
Speaker
And I was like, awesome. Cool. Wow. Like great. So I sit down and do like an initial interview to give me a take home assignment. I do the take home assignment. I return it. I do the follow up interview and you're like, okay, cool. Like, thank you. Um, we'll get back to you. They get back to me a little later saying, Hey, so we're not hiring for this position anymore. I was like, Oh, okay. But.
00:28:23
Speaker
there's somebody else who was interested in you. And I was like, okay, I guess I'll just keep getting punted around. This is fine. And they're like, it's so-and-so, like reach out and ask and, you know, like, we'll see what we can do. I was like, okay, sure. So again, I follow up, I send in the email and I was like, hey, I'm supposed to talk to so-and-so. And I hear nothing, literally nothing. And randomly I get a phone call and I was like,
00:28:50
Speaker
When you get a phone, they just called you out the blue. I was still old school and intimidating. And oh my gosh, why do, why do people do that? And also it was like an unknown number, right? So I was like, do I pick this up? I mean, luckily I was like in my interview mentality. So I was like, let me just pick it up in case it's like a recruiter or something. And I picked it up and they're like, Hey, this is so-and-so from Caesar's palace. And I got your resume from so-and-so and wanted to talk to you about this position. I was like, okay.
00:29:21
Speaker
And we talked about it and, you know, it was kind of outside of my comfort zone, actually. It wasn't quite exactly what I wanted to do, but I was like, you know what? Let me just get my foot in the door. Like, let me just, let me just do this. And they're like, okay, cool. You seem like a decent fit. Um, we'll, we'll get back to you. I was like, okay, cool. Thank you. No, no, nothing. I can't even send a thank you email. Cause I didn't even get their email. Like I just like had no idea. So I just like emailed the same contact person.
00:29:50
Speaker
This could have been like a prank call for all you knew. It could have been a total prank call from a friend or something. And then a couple of weeks later, they're like, can we do a follow-up interview with the next person up? And I was like, sure, I'll do a follow-up interview. And we chit chat. And then we get along great. And it was a good interview. And they're like, awesome. We think you'll be an excellent fit for the team. And I was like, awesome.
00:30:15
Speaker
Let's do it. And so we, you know, long story short, I, you know, started working at Jesus Entertainment shortly thereafter, after being redirected to three different teams and finding a completely different department to work for. This sounds like that fairy tale. Like the first job was too small. The other job was too big. This job was just right.
00:30:41
Speaker
It's a real Goldilocks job. You are the Goldilocks of Caesars. Yeah, it was great. It's good fun. That's a wild story. Just a phone call out of the blue. Okay, so you're saying that this job wasn't exactly what you were looking for. What specifically was that?
00:31:04
Speaker
Yeah, it was more focused on SQL, which is a database querying language. It's called structure query language. Hopefully I said that right. And yeah, it was much more on the side of database management and data, data engineering. And it wasn't, you know, it was a little bit of analytics, it was a little bit of, a little bit of Python.
00:31:27
Speaker
It was not necessarily the data science that I wanted to do, but I was like, you know what? It's a data job. It's in the data field. It'll give me some insight into how things are run. And so I was like, sure, let me go for it. Let me just go for this job and try it out.
00:31:48
Speaker
No regrets. I see no regrets here. So tell me about your day in and day out at Caesars because I remember in our pre-interview, you know, I'm just gonna let you talk. What was your day in and day out at Caesars? What were you specifically doing?
00:32:03
Speaker
putting out fires all the time. Basically what the team that does is there are asks for data, right? So we don't necessarily analyze the data at the very end. We do some, but not a ton. Really the main goal of the department is to make sure that the analysts get data that they need and the times that they need it.
00:32:24
Speaker
And so you actually get to work with a lot of the backend side of things and you have to build reports and things like that. So day in and day out was answering emails about, Hey, why isn't this table working? And it's, Oh, because it broke. Let me fix that for you. And to fixing that might look like, um, making sure that the table name is correctly referenced in the query and making sure that the computers that are running the processes like run correctly. Right.
00:32:50
Speaker
it could also just mean like, hey, like this pipeline broke down to do some research constraints. Like, can we optimize this? And so it was a lot of SQL, which I was not necessarily the most comfortable with at the time. I mean, I've done it enough to be decent enough to understand what's going on. And yeah, a lot of it is just kind of rewriting, optimizing other people's queries, making sure that things that can be automated become automated. There was a lot of that. There was a lot of building
00:33:18
Speaker
internal tools for automation, actually. And so day to day was very interesting to say the least. And I loved hearing about that initially. When I was looking for jobs, I was pretty much open to anything. There were certain industries like gambling that I didn't want to solve problems in because I think gambling, for me personally, is a huge way. It's not how I want to spend my money.
00:33:46
Speaker
And I didn't really want to solve problems for industries that I didn't think were worthwhile. That being said, hearing what you did, it made me really interested. It separated the actual act of gambling from just observing people. So maybe gambling is in my future. I don't know, but it is definitely going back to you saying that you like studying brains is definitely.
00:34:15
Speaker
a certain type of person. Yeah, you definitely have to. And I don't know, I think we don't really think about it too much, you know, the the ethical moral implications of the jobs we pick. But, you know, I think that there's a obviously it's weird to be part of an industry where the goal is to make you waste copious amounts of money. Every industry is trying to get you to do that, right? Like, obviously, but gambling has a certain kind of
00:34:43
Speaker
special way of making you do it, which, you know, is not the most agreeable. And I can definitely understand wanting to make sure that you're in an industry that you feel comfortable in. I definitely did not necessarily say, oh yeah, I love gambling. And I was very honest. I was like, you know, gambling is gambling. And it's not for me. It's interesting from a
00:35:07
Speaker
kind of data and people behavior standpoint, but it's not something I'm going to necessarily promote day in and day out. And I think that most of the people who work for the casino are actually more interested in how do we optimize the experience. Maybe back in the day, some people like maybe the CEO are like, yeah, how do we get these people to gamble more? And really, a lot of it is
00:35:37
Speaker
How do we, it's like every business, how do we spend the least amount of money to capture the largest audience to do the thing that we want them to do? You know, and thankfully this, oh, by the way, this is a kind of a, not a shameless plug, but prefaces with, um, there is a lot of huge initiative for responsible gambling, especially with online gambling. And so there's actually.
00:36:00
Speaker
automated systems to suspend player accounts who we think are doing too much. And there's a variety of partners for that. But yeah, the caveat, I suppose, is that we're trying not to ruin your lives. Wow. So it's almost like the bartender cutting you off. Exactly. There is a bartender who now cuts you off from your digital slots.
00:36:26
Speaker
That's actually a great thing to hear. Yeah, again, I know there's some people who will just do some slots just to gamble to each their own. I just have no desire, but that is very fascinating and a really interesting insight into a space that I personally don't, being blunt, don't care about. But again, very interesting thing that they're doing there.
00:36:55
Speaker
happy to hear that, but you're not there anymore. You moved from California to New York City to work for our Department of Transportation that I pay a lot of tax money to. So I'd love to hear about how you interviewed with them. What brought you to your second job?
00:37:15
Speaker
Yeah, first of all, thank you for paying my salary. I appreciate it. I don't have a choice here. I don't have a choice. I appreciate the kind of generous donation that is made by every New Yorker. That is forced by law. Oh, gosh, that's so funny. Yeah, it is. Can I just say, quick aside, the discovery of a city tax boggles me.
00:37:41
Speaker
that the city of New York specifically takes money out, uh, borrows me. It is a privilege to live here for sure. That is, that is, that is their selling point for the city tax. I don't agree. Uh, but I will say, Oh, I don't think it's a selling point. I just think it's something that you just deal with because you get to live in New York. And I'm New York or nowhere. I know I'm, I will, I don't,
00:38:09
Speaker
foresee myself ever leaving. Granted, I don't know what my future holds. There might become a reason, but I am New Yorker nowhere. And if that requires paying a city tax, well, you can go to any other city. That is such a New York attitude, by the way. Every New Yorker I've ever met is the city is terrible. Everything's everything's horrible here. The taxes are terrible. But I would. But it's New York. And that's how we do it here. And I don't want any other way. And I was like, you guys have Stockholm syndrome. You need to figure it out.
00:38:39
Speaker
I think we have. We just let Stockholm Syndrome run wild. The culture of New York is I'm a New Yorker. Nothing's going to change. You know what? It's a good personality. The experience, however, was kind of interesting and much more traditional, I think, in the sense of how these things are accepted. Quite tedious.
00:39:04
Speaker
You do an interview, you finish the interview, you get a take-home assignment that they say, okay, when do you want to start the assignment? I was like, this time. It's like, great. You get two hours and you must email it back within the two hours. I was like, okay, that's stressful, but I'll do it. That's very stressful. No, it's more than, but you know, you stress out a little bit. And what's worse is I couldn't download the file and I had to like scramble and I was like, Hey, this isn't working. And they're like, Oh, uh, sorry.
00:39:35
Speaker
As soon as I did that, follow-up interview, wait, wait, wait, wait. Randomly, as I'm having lunch with my now brother-in-law, I get a phone call. Again, these people with the random phone calls, no heads up. Stop, please, record, email us. Nobody wants a phone call out of the blue, unless it's like our grandmother, or maybe, I guess, our parents. You can't just call us. Text us first.
00:40:04
Speaker
Oh, what's that? Yeah. So I get, I get a phone call and they're like, Hey, we will, you know, we, we feel pretty good about you. We think you, you're going to be a good fit. Thank you. We want your position. I was like, great. Um, why don't you send over a contract and I'll take a look at it. Um,
00:40:25
Speaker
Well, first of all, they send a off to New York City, by the way, let me tell you about this. So they send you an offer letter, not a contract and offer letter. And you say, yes, I'm willing to accept this offer. And they're like, great, we'll get back to you. And it will get back to you. And then I guess there's an initial approval that has to happen. And you wait a few months for that.
00:40:51
Speaker
That was the first phone call. I was actually at work at that time to give me a call and say, hey, can you just offer that? I was like, sure. I return the offer letter. I wait, wait, wait. Get a phone call like a month or two later. And they're like, hey, so heads up. We're now heading to the next phase of the process, which is a
00:41:14
Speaker
unknown period of time. And I was like, what do you mean an unknown period of time? I was like, yeah, so there's a oversight committee that has to kind of go over your resume now. And I was like, wait, so do I have the job or don't have the job? They're like, you kind of have the job. I was like, awesome. So how long is this going to take? And they're like, well, anywhere from six months to a year or so. And I was like, or so? Yeah.
00:41:39
Speaker
You've seen it take a while and I was like six months to a year so much can happen I was like wait Yeah, they're like wait so Okay, and yeah, we'll we'll follow up after you know, but just wanted to be updated, you know, we're moving forward. I was like, okay Thankfully did not take six months take them about three and ish three ish months Still a really long time. Yeah, fair a long time. It's like three ish or so months
00:42:09
Speaker
No, I think it's like four, four, four-ish months. Then they're like, great, now you have to do all this paperwork and a background check and da da da da da.
00:42:19
Speaker
And that took a year, yes? That took about, you know, yeah, that took about a decade. That part wasn't so bad, actually. And then I was like, they're like, great, when can you start? And I was like, well, I got married soon. You know, they're like, OK, that's fine. We can wait till after that. I was like, cool. I also kind of want to finish a project here. Can I start in like, this is June. I was like, can I start in like September? And they're like, sure. And I was like, really? They're like, yeah, you can start.
00:42:48
Speaker
They were like, this is how wonderfully run the city is. They're like, you know, you can kind of just start whenever. And I was like, really now? Interesting. But no, I chose September because I had to take care of some stuff, you know, first at home and then they're like, great, we'll see you in September. And I was like, awesome. It was kind of
00:43:13
Speaker
interesting how spaced out everything was. And there was, there's no feedback. There's no update. They kind of just wait and see what happens. And here you are in New York. You just kind of appear. That's incredible. So when you were interviewing, were you still in California? I was. Okay. So they expected you to move here then because they want New York City employees in office.
00:43:39
Speaker
Correct. I was, uh, alerted to the fact that it was a mandatory, you must live in New York. And I was like, yeah, it's an adventure. I'll do it. Sure. I say so that's maybe why they allowed you to start a little later so that you could move here. I got the sense that things are pretty fast and loose in the department of transportation. And as long as it's reasonable, it's okay. Uh, yeah, I think part of it was like the, um,
00:44:07
Speaker
You know, the person who was, who was hiring me, like also had like some vacation lined up in August. And so they were going to be out for a little bit and they understood I had a lot of life stuff to kind of figure out. And I could still kind of start doing the onboarding paperwork anyways, remotely. So it didn't quite, quite matter that I was there right straight away. And so.
00:44:29
Speaker
Um, we kind of worked out it, you know, was a bit of a journey. It was quite a long path to, to do this whole like interviewing process with them. And so kind of glad that it's over now.
00:44:44
Speaker
For me, I'm glad it's over. These are my tax dollars again. So I'm glad things worked out for my sake. This is all about me, Tim. Clearly, I'll be. That was a joke. Yeah. Your tax dollars aren't enough because I still had to pay a processing fee to get my paperwork processed out of not only a money order, but also out of my first paycheck.
00:45:09
Speaker
New Yorkers, you should be outraged. Outraged. I mean, I didn't have to pay for it. Okay, well, no, that is absolutely ridiculous. This being said, okay, you're working for projects on city bike. So if you're not in New York, or if you don't know what city bike is, Tim, would you give us what city bike is in a sentence? Yeah, so city bike is one of many kinds of shared mobility.
00:45:38
Speaker
And so if you know what that means, it's basically like the lime scooters and things like that. Like that's all considered shared mobility. City bike is a specifically a docked bike share program where you take a bike and you ride it from station to station, right? So it's not like.
00:45:55
Speaker
It's not like the scooters or other bike systems where you kind of just like ride it wherever you want and drop it wherever you want. It has to be taken from point to point. The city bike program is not managed by Citibank. It is sponsored. It was originally sponsored by Citibank, hence the name Citibank. However, it has had many owner changes over the years. It is currently owned by Lyft. And so, yeah, and so you can actually get Citibank from your Lyft app.
00:46:24
Speaker
And it's quite cool, you, I believe it covers all of Manhattan. It covers parts of the Bronx now, kind of like the southern part of the Bronx. I have one outside my building. It covers most of Brooklyn, parts of Queens, not a whole lot of Staten Island. Is that all five boroughs?
00:46:46
Speaker
Yes. Delphi is all fiber. Yeah. And that makes sense because those are Staten Island. A lot of people have cars and same with people in Queens. So it would make sense that Manhattan and Bronx and Brooklyn, like those would be the heavy hitters. So tell me what your day in day like is with city.
00:47:07
Speaker
Yeah, so I commute half the week. I sit down and kind of recently have been working on data projects that look into ridership behavior. And so what that means is, we're basically just monitoring how people are using the system and from things like
00:47:31
Speaker
What kind of bikes do people prefer? What is the equity of the system like, right? Because at the end of the day, the goal of a private company owning city bike is very different from the goals of the city. And the city's goal of the program has been, or always will be to make it a public utility, right? Public good. It's not about generating income necessarily, which is kind of at odds of a
00:47:59
Speaker
corporation who is trying to make a profit. And so we are fighting that. That is interesting. I mean, it's great to hear because it connects so many people. I have so many friends that use it and love it. Yeah. In a very capitalist country, hearing about something that doesn't want to generate a profit necessarily as its first goal is mind blowing to me.
00:48:26
Speaker
Yeah, I mean, we have to look at whether the program itself is sustainable. Obviously, like, we can't sink insane amounts of money into it. No. No matter how much of public utility it may be, right? Those are your tax dollars, Alyssa. Tax dollars again. Again, all about you. This is your podcast. Thank you. Wow. You're the host.
00:48:50
Speaker
I am the host, but these are definitely my tax dollars. So let's get back to talking about. And so there is a focus on whether the program, and there is a lot of discussion about how healthy is the city bike program. What does ridership cost look like? What does the system cost look like? Um, those are kind of bigger projects that are looming in the near future. Um, actively currently we're kind of interested in how
00:49:20
Speaker
people choose to use the system. And so there's this kind of new initiative from Lyft where they.
00:49:28
Speaker
For those of you who don't know, you can buy a annual subscription to City Bike, which basically gives you free bike rides on a manual bike. So like a normal pedal bike, you just kind of ride that around town. And then a lower cost on the full electric e-bike. The gray ones you may see zipping around town, those are electric e-bikes.
00:49:53
Speaker
Um, there was a park where if that e-bike was the only bike, then you could get it for free as an annual member.
00:49:59
Speaker
Um, Lyft decided that that's too expensive. And so they've changed it where if you are a subscriber, you now have a choice to either take the bike out for free in a kind of low power mode where the bike basically just compensates for its weight. Cause it is quite a heavy bike. It's like 60 pounds, which is very heavy for a bike. Um, or you can pay still pay for the fully electric, um, kind of.
00:50:26
Speaker
you know, writer mode. And so one of the questions we're asking now is, does this impact writer decisions? How are people changing the way they use the system? Are they changing the way they use the system? How does this impact people who are
00:50:43
Speaker
using the equity kind of subscriptions right so there's a lot of local initiatives to give those and kind of lower income neighborhoods cheaper or free subscriptions because it would be inaccessible to them otherwise and so.
00:51:01
Speaker
I mean, the biggest question always is how fair is the system and how equitable is the system? And does it work in the way that it's intended by allowing people who normally would struggle with transportation greater opportunities, right? We talk about the first mile and the last mile.
00:51:19
Speaker
which is basically, are people able to use the bike to get to and connect to another transportation system that they normally wouldn't? And they can use the bike to finish a ride from a transportation to a place that they normally wouldn't be able to get to. So that's a lot of the kind of day in and day out analysis that we do. And I'm sure to someone looking to study data science or analyze data, that would be
00:51:41
Speaker
Those types of situations would be very, very fascinating to many. What's some of your favorite things about your job? Like what do you really look forward to working on when you go to work every day? I think that the biggest draw for me and you kind of have to, again, be a very special kind of person to work in government. You have to understand that it is not
00:52:06
Speaker
the glitz and glam of the tech world, right? For the most part, I'm sure there's, I'm sure there's agencies out there that do very well for themselves. You have to really be dedicated to the idea that you're serving a public good, right? It's called, you call it a public servant for a reason. And I think the thing that really keeps me currently in the job that really makes me want to be there is this idea that
00:52:37
Speaker
The work that I do is contributing directly to the potential life or data of a public system that impacts the lives of many people. And I think that when you consider what kind of impact you may have in your career, you know, obviously think about yourself and your needs and what kind of financial goals you may have or lifelong goals you may have, but
00:53:04
Speaker
At the end of the day, the thing that will keep you going at your work is do you enjoy what you do? And for me, having come from academia, having taught, having always kind of been a person who enjoys doing this sort of thing, being able to work with and in the public space is quite, quite an exciting opportunity.
00:53:25
Speaker
which I hope to continue. I'm quite new. So I'll be frank, there isn't a whole lot for me to work on at the moment because I am quite new to New York. But I am excited for the possibilities. And I hope that those possibilities come to fruition and that, yeah, you have to really just decide for yourself, like, yeah, you know what? I love my job.
00:53:53
Speaker
You know, this is what I want to do. And, and, and that I really do enjoy this because I get to make a positive, lasting impact on, on those around me and those in the city door, even though I may not know them and kind of more selfishly, it's kind of cool to walk around like cityway. I work on that, you know, that's a very cool thing to feel like seeing your product out there. And I can speak for some of my friends and colleagues. They love to be like.
00:54:24
Speaker
it gets them where they need to go and it's a better option to them than the subway. So you are, Tim, making an impact in the city, even though you just moved here, as I talk as a transplant who would be judged by a real New Yorker. So with that being said, we are coming up on time and I would love to know what's next for you. You are making moves with government as a public servant at Citibike, but what do you want next?
00:54:54
Speaker
That's a good question. I'm not sure. I am currently still exploring the exact breadth of the space within the city, right? And while it is very cool to work for the city, what I really care most about is my ability to grow.
00:55:17
Speaker
And so if you are a growth driven person, then you're constantly thinking about the work that you're doing and how it expands your skills. And so for me, I'm very interested in is the work that I'm doing not only
00:55:37
Speaker
meaningful, but also is it meaningful for myself? Am I growing from this? Am I learning from this? Am I able to take what I have and apply it to new things? Am I being challenged? It kind of circles back to, are there ever moments of work where I feel stupid?
00:55:54
Speaker
And so I think for me, the next thing is seeing how this plays out, you know, seeing what I can learn and then picking the next industry or company that I might be interested in learning about and then doing things for still within the room of science, data science, of course. But, you know, I think that I'm trying to keep focused on the learning aspect, but also look forward to what other opportunities and issues are out there.
00:56:25
Speaker
And I'll say something very quickly, which, again, may not be traditional career advice, but even if you have a job, keep applying to new jobs. Just, you know, like once a month, apply to a few jobs here and there, right? Keep your resume updated, keep your skills updated, right? And then just keep applying.
00:56:51
Speaker
That's how you get the most growth. Don't switch a job every three months maybe.
00:56:56
Speaker
Well, with your track record, it takes six months to a year to get a job. Right, right. So, you know, about six months then you want to start applying for the next one because that's about how long it'll take you to get a new job anyways. But really, if you want the most growth, not only in terms of salary, like number one, people who switch jobs every two years tend to have much higher salaries and people who stay the same job for 10 plus years. That's number one. Number two.
00:57:23
Speaker
Changing companies is the best way to grow your grow. You can learn new environments, new skill sets, new problems, new approaches, new solutions. So, you know, make sure you're doing that. You know, make sure you're challenging yourself and you're choosing to plan out your life in a way that allows you to keep changing.
00:57:49
Speaker
Or I mean, if you're very happy with the art, don't ignore me and just stay where you are. Because if you love what you do, then like, please, like, don't, don't feel like you have to change jobs. Conversely. Yes. I think Tim, there's a lot of wisdom in what you said.
00:58:04
Speaker
I'm sure people will take what they want from this. And yes, I agree. There is something to be said for constantly challenging yourself, whether that's getting a new job or seeking out a different opportunity between different projects at the same job. And with that being said, would you be open to having people connect with you on social media like LinkedIn?
00:58:27
Speaker
Yeah, let me verify my LinkedIn. Yes, if you like to find me on LinkedIn, my name is Timothy Liu. T-I-M-O-T-H-Y space L-U. Feel free to find me on LinkedIn if you like. I'm more than happy to talk to people about data science, what it takes to be a data scientist, and more about my experience at Springboard as well.
00:58:52
Speaker
Thank you so much for your time and sharing your story. I think a lot of people will take your unconventional advice to heart and for anyone else who's interested, if you have further questions for Timothy or myself or our Springboard alum and would like to be featured as a guest, please email me at alumnipodcast at springboard.com.