How To Learn Data Science? Tips And Career Advice from a Data Scientist (And Model)

foreign welcome back to another episode of talk Tech 
with Tiff in this episode I am sitting down   with Marissa who is a data scientist at Etsy 
we talk about the highs and also really dive   into the lows of being a data scientist her 
journey into data science and also speak about   her passions from becoming third runner-up 
Miss New York USA to modeling and so much in   between before we get into it though make sure 
to go check out my newsletter I linked it down   below it's a monthly newsletter that features 
unique job descriptions discount codes career   advice and always a little personal 
note for me okay let's dive into it welcome to talk Tech with Tiff the New York 
Edition where I am sitting down with industry   professionals to hear about their career Journeys 
and current roles I created this series to hear   from people who are established in the tech 
industry so that we can all learn what these   individuals do in their day-to-day jobs and 
the type of opportunities out there [Music]   hi Marisa how's it going good um it's a beautiful 
day in New York I know you came on a great weekend   I know I really did not too cold like a little 
bit chilly but super sunny I know and this is my   first time in Brooklyn actually oh yeah there's 
so many children on this block and I'm I'm not   used to that I live in dumbo so it's very like 
industrial and a lot of buildings and like Etsy   is there so um yeah it's very new refreshing I 
know I know this whole area people keep on telling   me it's very um family oriented I definitely get 
that sense yeah all my co-workers live here okay   yeah yes yeah a co-worker I did a conversation 
earlier with a co-worker of mine who has two   children and he lives like a few blocks away kind 
of thing yeah yeah yeah well thank you so much for   joining me today it's so funny it's so wonderful 
getting to to meet wonderful people like yourself   in real life and I know we were saying prior to 
to this podcast that you've been meeting a lot   of others as well recently content creators yeah 
it's so great in like in real life it's such a   like different experience you always like DM each 
other support each other on Instagram and then now   seeing each other in person it like makes it all 
real I I just met Maggie and data um Diaries I've   known Linda for a while yes um so yeah I know 
everyone has been like the same as they are I   know like as friendly as they are on Instagram so 
I love it I I totally agree and I feel like there   are so many you know you just listed some amazing 
women and there's I feel like there's so many   amazing women in New York that's what I was like 
I need to come to New York and meet you all like   yes it's just like jam-packed which I love yeah 
I know like New York SF yeah like Canada maybe up   and coming yes yeah up and coming we're getting 
there you know Toronto's surely but we're here   today to hear about you and you know your journey 
in tech and as a data scientist and um I'm sure   you get asked all the time about your role as a 
data scientist and and what it really entails but   tell me a bit about it a bit about your background 
what led you into data science uh I know you do   a lot outside of data science as well which we'll 
get to later because I think it's super important   to to cover those aspects as well but uh what is a 
day in the life like for a data science scientist   so at Etsy um a data scientist means a lot of 
different things so not only are you a coder   but you're also a problem solver a statistician 
and a domain expert so on my day-to-day like   the first couple of days of the week so Monday to 
Wednesday I'll be in a lot of meetings a big part   of being a data scientist is communicating with 
stakeholders and presenting your analyzes um and   storytelling with data so that's the first half of 
my week and then Thursday and Friday I'm more like   Focus days focused time to just heads down time 
to code and that includes like building tables   um with the logic our business logic and 
embedded into them also creating dashboards   based off of those tables and also experiment 
analysis which is the fun part of the job   experiment analysis yeah so I actually got 
into data science because I was fascinated   by experimentation and iterating 
on a product to make it better so   um we I have a couple of experiments going on 
right now and usually how that works is first   the ideation process with your product manager 
I'm working and as a data scientist you work with   different people on the team such as a product 
manager a product designer and Engineers okay   um so yeah first is the ideation process with my 
product Squad and then we go into launching the   experiment and we have an experimentation platform 
at Etsy so it has all the key metrics in there to   measure for um like a time period like let's say 
two weeks that's usually um how we test each of   our new features and then by the end of the two 
weeks I will report and conclude the experiment   and um like there will be a financial impact and 
a customer impact so I measured that at the end   and do like a post analysis wow that is super 
interesting and I love how you said uh it's   something you've always been interested in with 
around experimentation and that's kind of how   kind of going back on that note really how did 
what is tell me a bit about your background what   led you what was your schooling like like 
how did you kind of discover data science   um so I grew up in the Silicon Valley okay 
and that's that's All Tech I was surrounded   by Innovation growing up my dad is a director of 
infrastructure so he's a software engineer yeah   um and I I grew up really loving Math and 
Science um so when I went to college I graduated   with a it degree um but I didn't discover 
data science until I went to Grace Hopper   celebration which is the largest celebration uh 
and Gathering of women technologists in the world   um so that's where I discovered data science 
it was the track that interested me the most so   so when you're at Grace Hopper you follow a 
track of sessions and I learned so much about   experimentation like multivariate experimentation 
and um was just so inspired I never knew that this   was um a part of software engineering because when 
you major in computer science you have to find   your specialization yeah right yes and so that's 
where I was kind of lost like I didn't know I was   more like a generalist yes and at Grace Hopper I 
found data science I fell in love with the idea   of experimentation yeah um and yeah the rest is 
history wow I've never been to the Grace Hopper   conference which is so sad to say yeah yeah but 
it's on my it's on my like very near bucket list   like hopefully the next one um I think because the 
last two years I don't even know I think last year   it was in person right uh this year was in person 
and then the past two years was virtual virtual   yeah it's way worth it to go in person yes and 
yeah next year we'll go like as speakers I love   that yes yes putting that out there yeah that's 
our goal for next year yeah yeah we're putting it   out there I love it you went to Grace Hopper after 
you this all occurred after you graduated college   or was it during it was during my sophomore year 
of okay nice nice and then so from there did you   did you do an internship first or how did you 
kind of uh what was the next step from there   when you discovered data science um so after that 
I actually took a gap year in between community   college and university um I did a nano degree 
on um Udacity okay for data science so I that's   where I got my background in SQL and Python and I 
took that Gap year to focus on modeling full-time   that's when I first moved to New York it was 
really exciting and um I did internships after   um after my junior year of University I see I 
see and then it kind of just organically yeah   one thing to another that's very that's very cool 
um oh sorry and and during the I want to say like   these internships were like quote-unquote data 
science internships because at startups you really   wear many hats yes so Not only was I doing data 
science or like I also got to call it data science   because the the co-founders were like oh yeah you 
could you could call yourself whatever whatever   you want whatever whatever's got on the resume 
I love that that's something I always I always   like when people are first kind of starting out 
and it's similar to what I did when I was first   starting out is a great way to to really get your 
foot in the door or uh through internships there's   many ways but one way I found for myself and it 
sounds like for you as well is when you go with a   smaller company or a startup there's so much more 
typically more freedom or flexibility to kind of   try out different roles or wear many hats and and 
even kind of you know massage your title a little   bit you know to whatever you you fall in love 
with so that's really interesting that that's   how it happened for you um yeah I did everything 
at these startups from like data entry but also   like marketing and like front-end development 
so I was many things yeah yeah I love that   um as you know data science is such a such 
a popular role right now and everyone's just   like how do I become a data scientist I feel 
like um do you work with a question that that   I get asked not necessarily of course around data 
science but in general is uh you know do I have to   maybe they're later in life or different things 
like that with schooling do you work with anyone   who is say self-taught or did um kind of like 
you mentioned doing a nano degree online like   different walks of uh life yeah uh something 
that's really interesting at Etsy that I I love   about the culture is that there's like probably 
one or two people on the analytics team that have   a PhD in statistics but everyone else comes from 
very different backgrounds um so one of the senior   data scientists on my team he transitioned from 
being a ux researcher to a data scientist because   he was interested in the field and it's very easy 
to like internally switch within the company yeah   um the director of analytics she majored in 
political science worked the Hillary campaign   and now she works in analytics so I love that you 
there's a lot of like soft skills that you can   transition into data science or in Tech in general 
and I graduated in it which is not data science   but it's still the intersection at UC Santa Cruz 
it was described as the intersection of Business   Development and computer science and that kind 
of is like what data science is you feel like   a jack of all trades I I would describe myself as 
a jack of all trades um because like I said before   you're not just a coder you're a statistician 
Problem Solver I love that I think that's so   important to highlight too and and I don't know 
if you've come across this but I remember when um   not so much anymore but when I would tell people 
like oh what do you do and I say oh I'm a software   developer and and different people have different 
reactions but a common one was almost like oh so   you just you sit behind a computer all day and you 
don't talk to people I'm like that is the furthest   thing from the truth and I think you and I'm sure 
for you as well even like hearing about how Monday   to Wednesday is a lot of meetings and you need 
so many soft skills you've got to utilize so many   soft skills as well right yeah um a lot of my job 
is actually like communicating with stakeholders   yeah and if um I find that being a good data 
scientist is asking really good questions and   sometimes you kind of have to fish that out of 
your stakeholders like what are they really trying   to ask what is the real problem we're trying to 
solve yeah yeah wow that's really interesting   and then on that note kind of sauce what I what 
are some qualities or if someone's considering   getting into data science uh aside from of course 
you know the technical skills that they need to to   possess what are some other qualities that you 
think it makes a really good data scientist I   know you mentioned asking really good questions 
what else can I blow my nose yes of course um so I I think data science is just as much an 
art as it is a science and we both come from   the creative modeling field um and posing requires 
a lot of creativity yes um so when you are solving   a data science problem you it's you really have 
to take a creative approach and like let's say   you don't have enough data you have insufficient 
data you need to apply an algorithmic approach   in solving the problem and that's where the art 
form comes in using your different tools like   am I going to use a random forest or am I going 
to use linear regression to solve this problem   um so that's what I enjoy about yeah I love that 
there's it sounds like there's so many ways to to   solve a problem or to to I don't have the right 
term but to gather data it's not just a one one   linear way there's so many different ways and 
that's kind of the creative process too yeah yeah   you know we've been mentioning even mentioning 
a bit about modeling as well and I know you are   a three-time runner-up Miss New York right yes 
I was a third runner-up okay USA 2021 amazing   um or 2022 and I'll be competing again this next 
year so hopefully hopefully we'll be Miss New York   USA 2023.

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