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How to choose between software engineering and data science | 5 Key Considerations

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How to choose between software engineering and data science | 5 Key Considerations

Tina Huang 22.07.2020 438 071 просмотров 18 714 лайков обн. 18.02.2026

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Software Engineering vs Data Science? Last year, I made a choice between a software engineering and a data science position. In this video, I outline 5 key considerations that helped me choose between software engineering and data science. Hopefully it helps you make the choice as well! 🔗Affiliates ======================== 365 Data Science: https://bit.ly/3tIUBCY (link for 57% discount for their complete data science training) Check out StrataScratch for data science interview prep: https://stratascratch.com/?via=tina Google Data Analytics Certificate on Coursera: https://bit.ly/33tYQYA 🎥 My Filming Setup ======================== 📷 camera: https://amzn.to/3LHbi7N 🎤 mic: https://amzn.to/3LqoFJb 🔭 tripod: https://amzn.to/3DkjGHe 💡 lights: https://amzn.to/3LmOhqk 📲Socials ======================== instagram: https://www.instagram.com/hellotinah/ linkedin: https://www.linkedin.com/in/tinaw-h/ discord: https://discord.gg/5mMAtprshX 🤯Study with Tina ======================== Study with Tina channel: https://www.youtube.com/channel/UCI8JpGrDmtggrryhml8kFGw How to make a studying scoreboard: https://www.youtube.com/watch?v=KAVw910mIrI Scoreboard website: scoreboardswithtina.com livestreaming google calendar: https://bit.ly/3wvPzHB 🎥Other videos you might be interested in ======================== How I consistently study with a full time job: https://www.youtube.com/watch?v=INymz5VwLmk How I would learn to code (if I could start over): https://www.youtube.com/watch?v=MHPGeQD8TvI&t=84s 🐈‍⬛🐈‍⬛About me ======================== Hi, my name is Tina and I'm a data scientist at a FAANG company. I was pre-med studying pharmacology at the University of Toronto until I finally accepted that I would make a terrible doctor. I didn't know what to do with myself so I worked for a year as a research assistant for a bioinformatics lab where I learned how to code and became interested in data science. I then did a masters in computer science (MCIT) at the University of Pennsylvania before ending up at my current job in tech :) 📧Contact ======================== youtube: youtube comments are by far the best way to get a response from me! linkedin: https://www.linkedin.com/in/tinaw-h/ email for business inquiries only: hellotinah@gmail.com ======================== Some links are affiliate links and I may receive a small portion of sales price at no cost to you. I really appreciate your support in helping improve this channel! :)

Оглавление (6 сегментов)

0:00 Intro 133 сл.
0:45 Building vs Discovery Mindset 166 сл.
1:50 Roles 293 сл.
3:15 Salary 292 сл.
4:57 Coding 163 сл.
5:48 Entry Barriers 410 сл.

Intro

last year i was fortunate enough to have two internship offers one from amazon for software engineering and the other from goldman sachs for data science i ultimately chose to go with data science at goldman sachs and now i'm a full-time data scientist at one of the companies at feng so today i'd like to go into more detail about the differences between data science and software engineering and also how i made the decision in choosing between the two the five key considerations i'd like you to think about is first having a building versus discovering mindset second how well-defined do you want your role to be third career progression and salary fourth how much do you like coding and finally the entrance barriers between software engineering and data science so

Building vs Discovery Mindset

firstly building versus a discovery mindset so software engineering is very much around building using engineering tools as well as computer science and programming skills the products that you build can be games systems websites or applications for example building youtube so data science is much more focused on discovery you use a bunch of tools in computer science and programming math statistics as well as general scientific insights and methods in order to extract insights from data and then using those insights to drive impact in both business and products data science rules can also be much more specialized into machine learning roles or say data mining and all of the between all of these different sub rules the thing in common is that they're all very discovery focused you're always trying to discover things from the data and then doing something with those insights the first thing i'd like you to think about is are you more passionate about building products or discovering insights

Roles

the second key consideration is how well-defined do you want your role to be in general software engineering is a very well defined role compared to data science and that's mostly just because the office software engineering has been around for a lot longer than data science in most companies you have a pretty good idea of what your role as a software engineer is going to be you're going to be working with a team of other software engineers to build a product to push bugs to push a bunch of changes that are happening and maintaining your product and you have more clearly defined roles you could be an ios developer android developer web developer front end back end like that on the other hand for data science it's a lot more varied there isn't that clear of a structure because it's just a much newer role data science is inherently an interdisciplinary field and it involves a lot of different components so you're going to be focusing on not just one thing you can be coding a model you could be even thinking about the question that you're trying to ask to begin with you also be thinking about how to communicate these insights so that you can present them to business leaders so that they can drive those insights into impact because it's also a less mature field each data science role can also be very different in my case i've actually worked at three different data science roles and each of them has been wildly different from the other so the question i'd like you to ask yourself is do you want a more clearly defined job or would you prefer something that's more interdisciplinary so the third

Salary

thing i'd like you to consider is the career progression and salary between software engineering and data science so for software engineering it's pretty well defined in terms of your career track you work as a couple years as a software engineer and then you can choose if you want to continue down that track and become better and better at your craft or you can become a technical manager and manage other software engineers for data science there's also specializations for example you can become a machine learning expert or you can become a domain expert say something like ads or you can become someone that helps business leaders drive insights some data scientists also ultimately become data science managers so the software engineering salary is already pretty set out for you so according to glassdoors on average it's around 92k and ranging from 63k to 134k the salary for data scientists would vary a lot more depending on the work that you're doing on glass doors the average is 113k ranging from 83k to 154k so even though it feels like the data science salary on average is higher from my experience it's actually pretty similar in fact if you're working as a data scientist your salary might be a little bit lower than that of a software engineer but in general though these two jobs are both amazing in terms of salaries and there's a lot of career progression so ask yourself if you want to have a more clearly defined career progression or do you prefer more flexibility i wouldn't overthink the salary component that much because both of these careers are really similar in terms of salaries and you can make a lot for both of them

Coding

the fourth thing i'd like you to consider is how much you actually like coding this is the more practical consideration but how you spend your day at work does matter a lot in the end and the reality is as a software engineer you're going to be spending a lot of time coding as a data scientist you might also spend a lot of time coding but you also have a lot of other things to consider such as brainstorming and formulating questions to ask thinking about maths and just reading papers and general research and articles finally communicating your insights to your manager and to business leaders i would say if you love coding a lot stick with software engineering if you see coding as more of a skill in order for you to discover insights and to drive impact then consider data science i'd like you to ask yourself do you like coding just for the sake of coding itself

Entry Barriers

itself the fifth thing i would like you to consider is the difference in entrance barrier between software engineering and data science so the reality is that data science has a higher entrance barrier when i was trying to get a full-time job i applied to a lot of data science roles and software engineering roles i think in total i applied to around 50 software engineering roles and about 10 data science roles and the reason why there's a discrepancy between those numbers is because i noticed that there was just a lot more software engineering jobs out there and of those 50 software engineering jobs that i applied to i got around 15 first round invites and for data science though i only got one so for my internship at goldman sachs i actually applied for the general summer analyst role in technology and then asked to work on more machine learning and data science based work as an entry-level candidate software engineering will be much easier to get an interview and ultimately land a job so if you want to go into data science it's definitely still doable i managed to do it it's just a lot more hustle and you really have to be much more committed to getting that interview and you have to probably think about some creative ways to actually get your foot in the door if you're still on defense between software engineering and data science i think this is a key consideration to think about because software engineering does have a much lower barrier of entrance so in summary i've went through five different key considerations in making that decision between software engineering and data science first a building versus discovery mindset second how well-defined you want your role to be third career progression and salary fourth how much you enjoy coding and fifth the differences in entry barriers i hope this video has been helpful in helping you make the career decision between data science and software engineering although honestly they're both two really great careers and you really can't go wrong choosing either of them i would also love to hear your thoughts so please message me leave a comment contact me in any way and i also actually just started making videos but i'm planning to make one to two videos a week i would also greatly appreciate any feedback you guys have and future suggestions for videos

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