I would argue we as society don't want crime to stop simply for the sake of crime stopping (or for prison labor), but ultimately because we want to feel happy and safe from harm and unjust treatment. The systems we design need to factor in the humanness of the police and their communities and make sure they are not set up in a way that loses sight of that bigger picture.

1. More short-term crime prevention than a system catching 10% of A's crimes and 10% of B's crimes (good!)

2. Enforce a societal belief that A is intrinsically better than B (bad!)

3. Disproportionately burden children, families, and communities in B than A, causing them to indeed perform worse in everything than those in A (bad!)

4. As a result of 2 & 3 it is not a stretch to say simply causing B to do more actual crime (potentially negating point 1 entirely)

If you believe that crime enforcement is not for the sake of vengeance but instead something done to improve the well-being, safety, and happiness of citizens, you may see that inequality=bad just as crime=bad. How to best solve this trolley problem is complicated but it's important that people are aware that it is complicated before firing off an answer.

Remote: Remote or on-site are both fine

Willing to relocate: Yes, anywhere in Canada

Technologies: R, python (including pytorch/sklearn/huggingface), SQL, HPC, linux, git, fastapi, C++

Email: (it's a gmail address) psvelayu

I am about to complete my PhD focused on unsupervised learning method development and application to large biological data. I have an MSc in experimental neurology and a BSc in chemistry (specialized in quantum/computational chemistry). I am very proficient with R and maintain a package on CRAN used by multiple research groups for clustering clinical patient data. I have a strong foundation in math and statistical learning theory. I'm open to applying my data analysis / statistics / technical writing skills just about anything (in Canada).