Hi everyone!
I hope everyone has been well and is having a good week!
Over the past few weeks I have spent a lot of time talking to two of my mentors and doing projects for class which has definitely helped me progress my programming skills, but more importantly has taught me a lot about data science and its applications. Today I am going to talk with you all about two paths I have begun down to give you an idea of what you can do with a career in data science, and to give you a better idea of where you would see data scientists in your everyday life.
The first route I want to talk about is entrepreneurship and mini projects. This is a great way of getting into data science and making some early money and building your resume. One of the mini projects I am getting involved with is potentially building a sports API. This project will occur in several steps. First we will have to collect the data using scrapers. This means we will create tools that search the internet for specific data about individual players and teams to give us all the data we need to create a story with. We will then sort the data using tables so we can better understand what we have. Part of this process will also involve cleansing the data, which is part of making sure we have what we want. Next we will spend a bunch of our time modeling the data to begin to summarize what the data is telling us. This will lead into identifying trends in the data, which is where we begin to actually pull information, such as what players are going to have an MVP season and what teams are going to go to the championship. These trends are what help us make strong predictions about the future. The final step, which is less relevant to this problem, is creating graphics and presenting and reporting this data outward. This would be a way later step and something that is not too important yet.
This process is a very general process for data scientists and will hopefully teach me a lot of new skills that I have yet to have any exposure to. I am aiming to be moderately proficient in Pandas, R, SQL and more by the end of this process. I am working with a few other people, two of which are my mentors and will be able to lead me through the process of designing something this large and complex. I am extremely excited for the opportunity and to see myself progress.
Another thing I wanted to talk about, or another career path that has become very prominent for data scientists, is working in finance. A lot of investment bankers who work at certain trade desks and with certain companies deal with assets and derivatives that are extremely quantitatively based. In order to best make predictions when making these trades and to best understand how the market is going to shift, bankers need to create models. This is where data scientists come in and this is a route that I think would be very interesting to go. Data scientists, in the process I outlined above, are able to create models that can try to predict where the market will go in order to make stronger investments and ultimately make more money for clients.
In addition to these two paths that I am looking at, one more financially focused and one more technically focused, there are limitless other career options for data scientists. In recent years almost every company has been hiring data scientists in order to create predictive models for their growth and to do a ton of other technical tasks. It is a career for people who are unsure what industry they would like to end up in.
In addition to all of this data science stuff, however, I have continued learning JavaScript and working on mini projects through the online class that I have been taking. I am currently working on building out a banking application that can transfer data between accounts. This involves a few more backend steps that I never knew before so learning that has been extremely fun. Additionally I have been continuously working on my Python skills through my class through PSU and through my own personal research into the language. We are currently working on designing functions in Python in my PSU class but I have been working a bit past that.
I hope you all enjoyed the update and I look forward to continuing updating you on my progress!
Images:
https://towardsdatascience.com/finding-a-quant-finance-role-e59991549922
https://www.pngitem.com/middle/iohxTR_people-sport-png-clipart-sport-players-transparent-png/