Scientist or Engineer

13 May 2022

Whats What

When I was first getting my toes wet with computer science the terms used for all the different fields or jobs can be confusing. After a few years I have began to understanding all the different areas within the discipline. Even though there is a wide range of career paths you can go down the one thing I have learned is that there are huge overlaps in the knowledge between the different pathways. Many of the careers will use the same programming language or development environment. Two of the more popular fields are Software Engineer and Data Scientist. Even between these two fields one can dig deeper into more focused sub careers.

Software Engineering

Starting off with the second word engineer. To be an engineer means to innovate new products. When I think of a career in software engineering I think of creating things such as games, web applications, and of course Software. A software engineer can be apart of front end development which involves what the user sees or backend development which is the inner workings the user doesnt necessarily see. This involves having multiple teams on larger projects each focused on the different ends of the project. In order to do this well one must implement two concepts first Coding Standards and second Agile Project Management. Both of these concepts in short are rules and or guidelines on how to preform duties within the project.

The Data Scientist Overlap

On a different career path you have a data scientist. This pathway involves using the scientific method to produce results on a particular question. This field doesnt always involve working with software engineers. However most software engineers will use results from a data scientist to upgrade or provide better results from the programs they are designing. Whether working with or without a software engineer the concepts from software engineering i have mentioned previously can be used on daily basis in a career such as data science. The first coding standards which outlines a way of coding just as the English language has nouns, verbs, adjectives, and punctuation. This concept is fundamental not only to software engineer or data science but to any field in the computer spectrum. The second is Agile Project Management. In data science just as software engineer you may be working on a team of people. You may be developing a software program to better analyze A data set. Having a project management style such as Issue Driven Project Management or for short IDPM. Will help the project become successful. Some guidelines to implementing IDPM include. Meeting twice a week, splitting up tasks into 72 hour chunks, keeping documentation of such tasks, assigning each task to a team member. Then grouping theses tasks into 7-10 day “milestones” which could be presented to a client or the case of data science begin testing a smaller subset of the data.

More the Marrier

These are just a couple examples of crossover between the different fields in Computer Science or should we call it Computer Engineering. O wait that’s a whole different field to get into. To sum it all up in the field of computers knowledge in one career path can be used as knowledge in another career path. When learning new things outside of what you are focused on there will always be ways to integrate the techniques between them. Sometimes it is even a necessary part of the job.