How do I maneuver from data science to software development?
I am a recent graduate w/ a degree in CS. I got decent grades, but was not able to get a job in software development but somehow managed to get one in data science at a major consulting company. Regardless, I have literally zero interest in this. I think one major reason I didn't get accepted for a development job was simply because there were few available jobs at an entry level that I could apply to, and that my projects portion(having no experience) was relatively weak for getting a more senior position, which is to me totally understandable.
My current job title is Software Engineer(though this is just a designation and in reality means very little) so I think I can work here for some time and simply massage my resume a bit on what I did at work, but I do believe there is a clock ticking and if I can't manage to get out of this particular path fast enough I could be pigeon-holed into it permanently. What do I need to do to make myself more attractive for development jobs? Other than working on projects, which I will begin dedicating more time to as I settle into this job.
Considering that you have a CS degree and your current title is software engineer, it's just a matter of applying for software development jobs and interviewing well. It's hardly a big pivot.
Data scientists are too comfortable with R, while software engineers won't touch it with a ten foot pole. So to move forward in the career you allude to, definitely use Python in your current role as much as possible, and push yourself with engineering-like tasks/skills (e.g. volunteer to work on that CI/CD pipeline, don't just use numpy but understand how it writes to memory, etc.).
Honestly the transition from data science to software engineering has seemed like an easy one to me. As long as you have language proficiency in the area you want to go into it's a much lower bar (on paper at least). In my past job hunts I've had to spend a fair amount of time filtering out software engineering positions to stay on the data science/ML/etc track.
By development, I assume you mean product development.
Generally for enterprise product development language like C++, Java are preferred. You don't need to develop own "project" to get better in programming. You can contribute to open source projects.
I would suggest to keep applying for development jobs. Polish your resume and cover letter.
There's always chances to change careers later. But there's also plenty of room and need for software engineering in data science. The real data scientists are often terrible software engineers, but they still need reliable software running on a reliable platform.
Very easy just start interviewing. Grind leet if you want to be serious about it.
Why no interest in data science?
How important are side projects for getting entry level jobs?