Rather than thinking of Data Science and SWE as two different fields, think of Data Science on a spectrum, with "Advanced Data Analyst" on one side and "SWE/Machine Learning Algorithm Engineer" at the other.
Data Science is a weird field. A lot of the jobs descriptions have similar keywords, but there is just a huge amount of variance in what the job requires. There are definitely a large number of Data Science roles where solving a business problem requires you to write a good amount of code for integrating with other systems, data ET(maybe L), building UIs, etc that really is about making the core algorithm consumable by business owners.
When you interview ask what the day to day of somebody in that role is doing. You'll be able to figure out fairly quickly where they fall on this spectrum. Find the one that fits what you want.
IME, at smaller companies they don't have enough people to have 4 people (a Data Scientist, a Data Engineer, a SWE, and a Business Expert) just to get a data science project from conception to production. That's all done by one person with help from a business expert.
Data Science is a weird field. A lot of the jobs descriptions have similar keywords, but there is just a huge amount of variance in what the job requires. There are definitely a large number of Data Science roles where solving a business problem requires you to write a good amount of code for integrating with other systems, data ET(maybe L), building UIs, etc that really is about making the core algorithm consumable by business owners.
When you interview ask what the day to day of somebody in that role is doing. You'll be able to figure out fairly quickly where they fall on this spectrum. Find the one that fits what you want.
IME, at smaller companies they don't have enough people to have 4 people (a Data Scientist, a Data Engineer, a SWE, and a Business Expert) just to get a data science project from conception to production. That's all done by one person with help from a business expert.