hey everyone so some of you may know but my first job out of college when i graduated two and a half years ago as a physics major was in data science and i've been at my first role as a data scientist for almost two years and i quit and now i'm still a data scientist but i moved to a tech startup that's under uber right now almost two and a half years in the field of data science going in straight out of college entry level i feel like there's so much you need to know there
are a lot of things i realized over time that i think may help you if you're trying to break into the field or even if you've been in the field for a while i think you might agree or have more things to add to the points i'm gonna go into and of course i'll hit on salary i don't have a cs degree i don't have a master's or a phd and when i first started i was a data science associate for a year then became a data scientist and then got promoted for a couple months
to senior data scientist where i left after i got the promotion a couple months after and now i'm a data scientist at drizzly so i'm just gonna go into all of the different things i learned as well as right after that a section on salary expectations for entry level data scientists and i'll just go into ranges for how much i made so let's get straight into it [Music] i'm gonna go into the five biggest points that i kind of realized while i was doing some soul searching about why i really like the data science field
and the first thing is that data scientists are not made the same like i feel like data science encompasses so many different roles like a data scientist at one company might be doing something completely different from a data scientist at another company for example you could be more a data analyst where you really work heavily in sql and do crazy sql aggregations window functions and like crazy things to create tables that you put into production or you could be really into data visualization or you could be heavy into machine learning where you really are building
your own custom models researching the underlying math behind everything and hybrid tuning everything like perfectly so that you have like the most perfect model that isn't over fit which i don't know if that exists there are so many different types of data scientists and honestly each data science project i worked on i felt like i gained a new set of skills entirely it's almost like i never have the same role even though i am a data scientist every single project is so different and it's interesting there are so many sides like even experiment design where
you have to help the business make data driven decisions there's a lot of money involved in doing market research or like doing an a b test with like advertisers for example advertising in one market and not the other to see if there's an actual incremental lift if the ads correlate to higher revenues it's just really interesting stuff there's so much to learn and i feel like every single project i've worked on and for the past two and a half years they're so different and i feel like i've worked on like 10 to 15 different projects
and gained all these skills along the way so it's just really cool that's what i love about data science it's not all cut the same so if you don't get a data science role because it's not technical enough or it's too technical just apply it to different companies like there's so many different kinds of data scientists and you're going to find where you fit in data scientists are in literally every industry you can be in finance you could go to tech market research consulting the world is really your oyster in data science which is great
the next thing data science is all about constant learning like if you want a job where you're gonna learn a set of skills and keep those set of skills forever and think that's gonna get you through everything it's not like data science is not the right place for you you're constantly learning new things whether it's like new packages coming up in python new things being added to your tech stack or just new projects where you're assigned a project or you find a business opportunity for a project that you don't have the right skills in you're
gonna have to gain those skills i'd say the first thing is that you really have to learn from the people around you right now at my company there's only like five or six data scientists and i'm coming from a company that had like five or six hundred and like a very large established monopoly almost my last company and then now i'm at a tech startup under uber and like it's amazing the people around me the senior data scientists the manager exact like everyone is super super helpful and i feel like i want to learn as
much as i can not just about data science and building skills which i do like every time i have a question i reach out to someone who is smarter than me which is basically everyone at my company to learn whatever i'm lacking so that i could do this project the best way i can but i also want to understand like what projects are required to add business value what's driving revenue for the company how can we add to the revenue of the company by creating data products especially the ones that aren't high effort you want
to get as much out as you can as a data scientist at least that's what i do right now in my role so it's really interesting moving back and forth another thing that just comes under the constant learning like i would just strongly recommend like which i'm sure you do already if you're a data scientist but reading towards data science on medium and just watching different youtube videos and i guess just keeping up with the different documentation for packages like there's always new things being added the third and probably one of the most important points
the ability to communicate as a data scientist is gonna take you way farther than you could ever think when it comes to data science i feel like your age your background none of that matters it's really about how effective you are at using the output of your models and how you use data and analyze data to really drive business decisions that is so important and the faster you can do that i feel like you just progress like so quickly as a data scientist when you start understanding the value of what you're putting out like if
you're just doing ad hoc analyses where someone's like hey can you get me that can you get me this and blah blah blah you just do those reports which trust me i've done because that's what being entry level is all about right understanding how you can drive further value by using data you already have and just creating new products and like utilizing all the resources you have to create something new and convey all of that to the business is just really really important like i think communication is really important the fourth this is where i'm
going to talk about pay a little bit but it's really that pace so different between industries and data science almost relating to the first point about how data science is different everywhere like i feel like some sections of data science particularly like machine learning deep learning they're not just buzzwords like people actually do that on the day to day and i feel like they get paid a lot to do it so data analysts generally make less data scientists generally make in the middle and if you're a data scientist specifically working with machine learning models and
building custom models that machine learning skill set which usually you get after working with several projects related to that or getting your masters or phd pays very well so that is also the same when it comes to industry so i was in market research for two years working for nielsen and in market research i can tell you like the pay is different from what the pay is in tech right if you're working at google microsoft uber like any of the big companies the tech packages are just different because they include stock options so you usually
just get a higher salary by virtue of the bonuses and the stock options market research and consulting and all of that like yes you're gonna get to a six figure pay but like it might not be high six figures like it would be in tech and if you go to finance and you're working in quantitative finance not at a bank but at a hedge fund i feel like banks pay like the way consulting does like i think tech pays better than most industries but then i think the industry that pays way better than tech even
if you still want to be a data scientist or use those quantitative skills is just quant finance like if you're going to be working as a quant researcher at a hedge fund like you're just going to be making a ridiculous amount of money 200 to 300 000 the pay is very different as are the interviews and the difficulty of getting the job like getting a job in tech is difficult getting a job as a data scientist anywhere honestly is pretty difficult but i'd say getting a job as a quant researcher like you just need a
lot of skills maybe more of an academic background having a phd you know it's just different but like the pay is different too and the last thing i just want to touch on that i realized in my first entry level job as a data scientist is that not having a cs degree doesn't really put you a disadvantage so i don't have a computer science like undergrad degree i have one in physics and i was really lucky that i took like classes in python and like i learned the computational side of astrophysics a lot of bayesian
inference monte carlo simulations like i feel like i learned the things i needed for data science and i got very lucky just machine learning models classifying the difference between a star in a galaxy like binary classification also just a lot of data analysis because we had to analyze all the data that came back from telescopes so really interesting stuff and i feel like i came with an advantage because i i could land interviews as a physics major i never felt like i was at a dearth of opportunity given the fact that i don't have a
cs degree but i will say i think jumping from data scientist to like a senior data scientist or a lead you might actually need a master's or something like that for that because i'm the only data scientist at my company me and one other person without a master's or phd so making that jump like just technically understanding the mathematical intuition that goes behind all the statistic models you use like learning all of that on the fly which is what i've been doing is totally doable but also just having a degree i think just propels you
much faster and higher and the pay is also obviously very different if you're a data scientist or senior data scientist at a tech company so i never really felt limited by not having a cs degree entry level like at all it's really about what you can do for the company and how well you can code and how well you can translate that code to business decisions but i think maybe further down the line that might make a difference like maybe i should get a master's degree part-time wink i don't know quick introduction before i start
talking salary which everyone's favorite topic right don't forget to smash that like button to let the youtube algorithm know this is useful and if you don't find this useful let me know why thanks so much [Music] so quick section about salary expectations because i feel like a lot of people would want to know this entry level i think data science honestly just pays really well entry level i'm going to give ranges and i have everything written down but i want to say everything's like location dependent let's say you're in a city like chicago or dallas
or like you know these are cities i've lived in you could expect like entry level if you have like you know python skills you understand the basics of machine learning and you do well enough honestly it's basically up to this if you do well enough to get interviews and get a job offer you could probably expect anything between like 70 to like 90k and this is like if you're not at a tech company if you're gonna go to a tech company like google microsoft like any of the tech companies it's like a space in technology
where it's like a silicon valley company just add like 30 to 40k to the range i just told you like probably like 110 to 130. like something like that i would say i don't know if that's like exactly entry level or year in you could definitely expect six figures easily very easily if you're going to a tech company and you're gonna be located in california like yeah a hundred thousand is definitely a given and if it's not you might wanna like think about the industry the company you're applying to is in in san francisco given
the cost of living the area the amount of taxes you're gonna pay that probably like equalizes down to like you know something between 60 to 80 in like a smaller city so very location dependent but yeah of course if you're going into a more analyst role to go into a data scientist role you could expect like a maybe like a 15 000 range lower than the 70 to 90. so going into like my shift in salary i'd say like you usually get bumps every like 10 to 12 months at least i did at my old
company it might be different now that i switched roles to a startup when i was at nielsen for two years where i was a data science associate data scientist and then got promoted to senior data scientists i'll just say my salary range like for all of that was between 80 to 110 and i lived in florida where the cost of living was extremely low like i honestly saved like 50 to 60 of what i made and invested most of it and recently i just bought a condo in chicago so i'm going to be moving to
chicago and that's where i'll be living with my current salary and i'll just say the range for my current salary is like 120 to 150 and that's like two and a half years into working in the field so i switched roles like i was at my first company for two years now i've been here at the startup for a couple months totally livable like i still save like 50 to 60 of what i make really healthy i think the fact that i don't live in the bay area and i can make that kind of salary
that switch between roles like there's a study where i think if you switch your job every two years you like make 50 more over time like which i i would say is true like you usually do get more but i will say now that i work for a tech company i also get the stock options which just adds to my annual which is also great but you don't see that until like a year into working and then you start getting vested monthly or quarterly depending on where you work so it takes a year for all
of it to hit and then you start getting invested on a more regular cadence but i would say it's definitely a good field and i'm not entry level anymore i guess because it's been two and a half years now but when i joined this company like i did join as a data scientist and not a senior or anything like i feel like senior data scientists at tech companies have like seven years of experience and like some sort of like master's degree or they just have like a lot of work experience so that's pretty much it
for everything about being an entry-level data scientist things i learned and salary expectations if there's anything else you would like to know please let me know comment down below i really think like anyone would be a good data scientist all you have to do is be curious if you're curious and you're really good at learning things quickly data science is like a great field it's lucrative it's really interesting the problems are always different the projects are always different never feels like the same job so it's really hard to get bored so if you have any
questions please feel free to let me know down below and keep a lookout for more videos like this thanks so much and i'll see you guys at the next video [Music]
