Data Science: Startup vs. Large Corporation

Key Takeaways

hello everyone ken here today I'm talking about the differences in the data science role at a start-up versus a large corporation I've worked as a data scientist and a data scientist manager at both startups and fortune 100 organizations and there's some pretty stark differences between the working experience in this role before I get into the meat here I'm gonna please remind you to like this video if you enjoy it really helps me spread and grow my channel also subscribe if you'd like to see more content like this now the first thing I'd like to talk about is the actual nature of the data science role in smaller startups usually data scientists are responsible for a lot more breadth in terms of activities so you're maybe not going to be doing data science all the time you could be helping with even marketing strategy or designing the infrastructure of the databases there's a lot of things you can do a lot of ways that you can pitch in and this is really great experience especially if you want to be moving into management or managing of other parts of the organization aside from data science down the road it's still a great place to learn data science because you understand the strategy of wire setting up certain analyses and why a certain project fits into the bigger picture of the company in large organizations big corporations the role of the data scientist is generally a lot more defined you're probably going to work in one fairly specific area with fairly specific constraints for example when I was at GE one of the guys I worked with his whole responsibility was to work on and improve the will the wheel wear model for locomotives so no I mean that was a cool job he absolutely loved it but his focus was very very specific in that area if a lot of tasks a lot of projects can seem overwhelming do this is totally a great option you can completely master one subject area and that can be the focus of a large part of your career culturally in a start-up things can happen very fast you can be working on one project you get it to where it's good enough and then you start working on another one you can pivot in terms of your strategy and the projects that you were working on before aren't necessarily relevant anymore and that's something to be prepared for if you like that fast-paced atmosphere this is absolutely something for you on the other hand large corporations things can generally happen a lot slower because of structure corporate culture there's generally a hierarchy and things have to get approved in order for them to actually get done so even to get access to the data source get preliminary approval to have a dashboard built this has to go through some approval process from the higher-ups and that can be a bit frustrating sometimes but it also means that you're gonna be working on projects that are very carefully curated so from a data perspective I think any organization big or small can have data quality issues usually larger organizations struggle with data because of legacy systems legacy things that they've been collecting that don't cooperate or integrate well with the new data that they have that's very relevant and useful so if you are going to have a wealth of data but managing it can be a bit difficult from a data science perspective on the other hand at a start-up usually there is not enough data you know there's some data collected but there's enough time or the function that you want to understand better it hasn't been around for long enough for you to be able to use this data in analysis so there's two different data challenges at these two different levels and you kind of have to figure out one this is very specific to the organization so what your organization and what the organization that you're looking at is struggling with and to what type of challenge that you like do you like working with sparse data or do you like cleaning cutting and manipulating data so that it can be a partial match and can be workable within your algorithms overall I personally prefer working in the startup environment better I really love data science but I love other elements of business as well I like management I like communicating with people and I found that in a start-up I had ownership of a lot more things and I was able to really make an impact for me seeing an impact in an organization is extremely extremely meaningful thank you so much for watching and please enjoy your data science journey